http://tahoesiliconmountain.com/
Tahoe Silicon Mountain, a network of entrepreneurs and professionals who live and work in the Tahoe-Truckee area, is pleased to welcome Dr. Christos Papachristos to present at Mountain Minds Monday: “Self-Flying Drones: On a Mission to Navigate Dark, Dangerous and Unknown Worlds”
Even with all our current technical advances, dangerous and unpleasant jobs are still a part of modern life. Imagine a world where flying robots could be used to navigate in any environment, under any possible conditions, and complete risky tasks that humans currently perform.
Dr. Christos Papachristos, Post-Doc Researcher at the Autonomous Robots Lab at University of Nevada, Reno, will be speaking about how, without the benefit of GPS or previously mapped environments, drones can be used in beyond line-of-sight operation to autonomously navigate, map and explore dark and dusty, partially sealed or underground, and generally visually-degraded environments like mines or nuclear waste sites.
Dr. Papachristos will discuss the use of regular cameras with flashers, inertial sensors, 3D-structure time-of-flight cameras combined with infrared cameras, ionizing radiation detectors, and the logic behind the algorithms that guide the drones on their missions.
You can learn more about the Autonomous Robots Lab here: http://www.autonomousrobotslab.com/
Mountain Minds Monday will be on Monday, October 9th, 6-8 pm at Pizza on the Hill, in Tahoe Donner at 11509 Northwoods Blvd., Truckee. A $5 fee includes pizza and salad. Before and after the presentation, there will be time for networking.
The event will also be livestreamed and available online as it happens on YouTube: bit.ly/YouTubeTSM
This month’s event is sponsored by New Leaders, Holland & Hart LLP, Molsby & Bordner, LLP and The Lift.
You can find us on LinkedIn and Facebook and at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
Real Time Object Detection with Audio Feedback using Yolo v3ijtsrd
In this paper, we propose a system that combines real time object detection using the YOLOv3 algorithm with audio feedback to assist visually impaired individuals in locating and identifying objects in their surroundings. The YOLOv3 algorithm is a state of the art object detection algorithm that has been used in numerous studies for various applications. Audio feedback has also been studied in previous research as a useful tool for assisting visually impaired individuals. Our proposed system builds on the effectiveness of both these technologies to provide a valuable tool for improving the independence and quality of life of visually impaired individuals. We present the architecture of our proposed system, which includes a YOLOv3 model for object detection and a text to speech engine for providing audio feedback. We also present the results of our experiments, which demonstrate the effectiveness of our system in detecting and identifying objects in real time. Our proposed system can be used in various settings, such as indoor and outdoor environments, and can assist visually impaired individuals in various activities such as the navigation and object identification. Dr. K. Nagi Reddy | K. Sreeja | M. Sreenivasulu Reddy | K. Sireesha | M. Triveni "Real Time Object Detection with Audio Feedback using Yolo_v3" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd55158.pdf Paper URL: https://www.ijtsrd.com.com/engineering/electronics-and-communication-engineering/55158/real-time-object-detection-with-audio-feedback-using-yolov3/dr-k-nagi-reddy
The goal of the project is to run an object detection algorithm on every frame of a video, thus allowing the algorithm to detect all the objects in it, including but not limited to people, vehicles, animals etc. Object recognition and detection play a crucial role in computer vision and automated driving systems. We aim to design a system that does not compromise on performance or accuracy and provides real time solutions. With the importance of computer vision growing with each passing day, models that deliver high performance results are all the more dominant. Exponential growth in computing power as well as growing popularity in deep learning led to a stark increase in high performance algorithms that solve real world problems. Our model can be taken a step further, allowing the user the flexibility to detect only the objects that are needed at the moment despite being trained on a larger dataset. P. Rajeshwari | P. Abhishek | P. Srikanth | T. Vinod ""Object Detection: An Overview"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23422.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/23422/object-detection-an-overview/p-rajeshwari
Real Time Object Detection with Audio Feedback using Yolo v3ijtsrd
In this paper, we propose a system that combines real time object detection using the YOLOv3 algorithm with audio feedback to assist visually impaired individuals in locating and identifying objects in their surroundings. The YOLOv3 algorithm is a state of the art object detection algorithm that has been used in numerous studies for various applications. Audio feedback has also been studied in previous research as a useful tool for assisting visually impaired individuals. Our proposed system builds on the effectiveness of both these technologies to provide a valuable tool for improving the independence and quality of life of visually impaired individuals. We present the architecture of our proposed system, which includes a YOLOv3 model for object detection and a text to speech engine for providing audio feedback. We also present the results of our experiments, which demonstrate the effectiveness of our system in detecting and identifying objects in real time. Our proposed system can be used in various settings, such as indoor and outdoor environments, and can assist visually impaired individuals in various activities such as the navigation and object identification. Dr. K. Nagi Reddy | K. Sreeja | M. Sreenivasulu Reddy | K. Sireesha | M. Triveni "Real Time Object Detection with Audio Feedback using Yolo_v3" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd55158.pdf Paper URL: https://www.ijtsrd.com.com/engineering/electronics-and-communication-engineering/55158/real-time-object-detection-with-audio-feedback-using-yolov3/dr-k-nagi-reddy
The goal of the project is to run an object detection algorithm on every frame of a video, thus allowing the algorithm to detect all the objects in it, including but not limited to people, vehicles, animals etc. Object recognition and detection play a crucial role in computer vision and automated driving systems. We aim to design a system that does not compromise on performance or accuracy and provides real time solutions. With the importance of computer vision growing with each passing day, models that deliver high performance results are all the more dominant. Exponential growth in computing power as well as growing popularity in deep learning led to a stark increase in high performance algorithms that solve real world problems. Our model can be taken a step further, allowing the user the flexibility to detect only the objects that are needed at the moment despite being trained on a larger dataset. P. Rajeshwari | P. Abhishek | P. Srikanth | T. Vinod ""Object Detection: An Overview"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23422.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/23422/object-detection-an-overview/p-rajeshwari
Autonomous Spacecraft Navigation with Artificial Intelligence.pdfheatblast616x
"Autonomous Spacecraft Navigation with Artificial Intelligence," explores the integration of AI technologies into spacecraft navigation systems. This cutting-edge approach enables spacecraft to operate autonomously, make real-time decisions, and adapt to dynamic mission conditions, revolutionizing space exploration capabilities.
IEEE CASE 2016 On Avoiding Moving Objects for Indoor Autonomous QuadrotorsPeter SHIN
Abstract - A mini quadrotor can be used in many applica- tions, such as indoor airborne surveillance, payload delivery, and warehouse monitoring. In these applications, vision-based autonomous navigation is one of the most interesting research topics because precise navigation can be implemented based on vision analysis. However, pixel-based vision analysis approaches require a high-powered computer, which is inappropriate to be attached to a small indoor quadrotor. This paper proposes a method called the Motion-vector-based Moving Objects Detec- tion. This method detects and avoids obstacles using stereo motion vectors instead of individual pixels, thereby substan- tially reducing the data processing requirement. Although this method can also be used in the avoidance of stationary obstacles by taking into account the ego-motion of the quadrotor, this paper primarily focuses on providing our empirical verification on the real-time avoidance of moving objects.
Integrated Hidden Markov Model and Kalman Filter for Online Object Trackingijsrd.com
Visual prior from generic real-world images study to represent that objects in a scene. The existing work presented online tracking algorithm to transfers visual prior learned offline for online object tracking. To learn complete dictionary to represent visual prior with collection of real world images. Prior knowledge of objects is generic and training image set does not contain any observation of target object. Transfer learned visual prior to construct object representation using Sparse coding and Multiscale max pooling. Linear classifier is learned online to distinguish target from background and also to identify target and background appearance variations over time. Tracking is carried out within Bayesian inference framework and learned classifier is used to construct observation model. Particle filter is used to estimate the tracking result sequentially however, unable to work efficiently in noisy scenes. Time sift variance were not appropriated to track target object with observer value to prior information of object structure. Proposal HMM based kalman filter to improve online target tracking in noisy sequential image frames. The covariance vector is measured to identify noisy scenes. Discrete time steps are evaluated for identifying target object with background separation. Experiment conducted on challenging sequences of scene. To evaluate the performance of object tracking algorithm in terms of tracking success rate, Centre location error, Number of scenes, Learning object sizes, and Latency for tracking.
Deep Learning for X ray Image to Text Generationijtsrd
Motivated by the recent success of supervised and weakly supervised common object discovery, in this work we move forward one step further to tackle common object discovery in a fully unsupervised way. Mainly, object co localization aims at simultaneously localizing the objects of the same class across a group of images. Traditional object localization detection usually trains the specific object detectors which require bounding box annotations of object instances, or at least image level labels to indicate the presence absence of objects in an image. Given a collection of images without any annotations, our proposed fully unsupervised method is to simultaneously discover images that contain common objects and also localize common objects in corresponding images. It has been long envisioned that the machines one day will understand the visual world at a human level of intelligence. Now we can build very deep convolutional neural networks CNNs and achieve an impressively low error rate for tasks like large scale image classification. However, in tasks like image classification, the content of an image is usually simple, containing a predominant object to be classified. The situation could be much more challenging when we want computers to understand complex scenes. Image captioning is one such task. In these tasks, we have to train a model to predict the category of a given x ray image is to first annotate each x ray image in a training set with a label from the predefined set of categories. Through such fully supervised training, the computer learns how to classify an x ray image and convert into text. Mahima Chaddha | Sneha Kashid | Snehal Bhosale | Prof. Radha Deoghare ""Deep Learning for X-ray Image to Text Generation"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23168.pdf
Paper URL: https://www.ijtsrd.com/engineering/information-technology/23168/deep-learning-for-x-ray-image-to-text-generation/mahima-chaddha
Object tracking with SURF: ARM-Based platform ImplementationEditor IJCATR
Several algorithms for object tracking, are developed, but our method is slightly different, it’s about how to adapt and implement such algorithms on mobile platform.
We started our work by studying and analyzing feature matching algorithms, to highlight the most appropriate implementation technique for our case.
In this paper, we propose a technique of implementation of the algorithm SURF (Speeded Up Robust Features), for purposes of recognition and object tracking in real time. This is achieved by the realization of an application on a mobile platform such a Raspberry pi, when we can select an image containing the object to be tracked, in the scene captured by the live camera pi. Our algorithm calculates the SURF descriptor for the two images to detect the similarity therebetween, and then matching between similar objects. In the second level, we extend our algorithm to achieve a tracking in real time, all that must respect raspberry pi performances. So, the first thing is setting up all libraries that the raspberry pi need, then adapt the algorithm with card’s performances. This paper presents experimental results on a set of evaluation images as well as images obtained in real time.
The 2020 ski season is just around the corner, but with COVID-19 limiting access to your favorite ski area, what is an avid skier to do? Backcountry skiing promises no lines, a limited number of people, and the allure of carving turns through fresh snow, but before you head out, it is essential to have a solid understanding of what it takes to get out there responsibly, sustainably, and safely.
Join Tahoe Silicon Mountain, a local network of entrepreneurs and professionals, today, November 9th, for a panel discussion with a team of backcountry ski experts to help educate you on the essential things you need to know before you strap on your skins and head out. Some of the key topics we will cover:
• Gear: What you really need to get started
• Avalanche Safety 101 and Local AVI I certification resources
• Lake Tahoe backcountry spots
Our panelists will Include:
Andy Rathbun, Administrator and Moderator for San Francisco Backcountry Skiers
David Reichel, Executive Director of the Sierra Avalanche Center
Emily Hargraves, Chief Executive Babe of Backcountry Babes
Vans used for getting outdoors range from simple vans to significant upgrades in 4 x 4 adventure vans, almost tiny homes. Nick Polinko provides insights he gained in making his enhanced van.
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IEEE CASE 2016 On Avoiding Moving Objects for Indoor Autonomous QuadrotorsPeter SHIN
Abstract - A mini quadrotor can be used in many applica- tions, such as indoor airborne surveillance, payload delivery, and warehouse monitoring. In these applications, vision-based autonomous navigation is one of the most interesting research topics because precise navigation can be implemented based on vision analysis. However, pixel-based vision analysis approaches require a high-powered computer, which is inappropriate to be attached to a small indoor quadrotor. This paper proposes a method called the Motion-vector-based Moving Objects Detec- tion. This method detects and avoids obstacles using stereo motion vectors instead of individual pixels, thereby substan- tially reducing the data processing requirement. Although this method can also be used in the avoidance of stationary obstacles by taking into account the ego-motion of the quadrotor, this paper primarily focuses on providing our empirical verification on the real-time avoidance of moving objects.
Integrated Hidden Markov Model and Kalman Filter for Online Object Trackingijsrd.com
Visual prior from generic real-world images study to represent that objects in a scene. The existing work presented online tracking algorithm to transfers visual prior learned offline for online object tracking. To learn complete dictionary to represent visual prior with collection of real world images. Prior knowledge of objects is generic and training image set does not contain any observation of target object. Transfer learned visual prior to construct object representation using Sparse coding and Multiscale max pooling. Linear classifier is learned online to distinguish target from background and also to identify target and background appearance variations over time. Tracking is carried out within Bayesian inference framework and learned classifier is used to construct observation model. Particle filter is used to estimate the tracking result sequentially however, unable to work efficiently in noisy scenes. Time sift variance were not appropriated to track target object with observer value to prior information of object structure. Proposal HMM based kalman filter to improve online target tracking in noisy sequential image frames. The covariance vector is measured to identify noisy scenes. Discrete time steps are evaluated for identifying target object with background separation. Experiment conducted on challenging sequences of scene. To evaluate the performance of object tracking algorithm in terms of tracking success rate, Centre location error, Number of scenes, Learning object sizes, and Latency for tracking.
Deep Learning for X ray Image to Text Generationijtsrd
Motivated by the recent success of supervised and weakly supervised common object discovery, in this work we move forward one step further to tackle common object discovery in a fully unsupervised way. Mainly, object co localization aims at simultaneously localizing the objects of the same class across a group of images. Traditional object localization detection usually trains the specific object detectors which require bounding box annotations of object instances, or at least image level labels to indicate the presence absence of objects in an image. Given a collection of images without any annotations, our proposed fully unsupervised method is to simultaneously discover images that contain common objects and also localize common objects in corresponding images. It has been long envisioned that the machines one day will understand the visual world at a human level of intelligence. Now we can build very deep convolutional neural networks CNNs and achieve an impressively low error rate for tasks like large scale image classification. However, in tasks like image classification, the content of an image is usually simple, containing a predominant object to be classified. The situation could be much more challenging when we want computers to understand complex scenes. Image captioning is one such task. In these tasks, we have to train a model to predict the category of a given x ray image is to first annotate each x ray image in a training set with a label from the predefined set of categories. Through such fully supervised training, the computer learns how to classify an x ray image and convert into text. Mahima Chaddha | Sneha Kashid | Snehal Bhosale | Prof. Radha Deoghare ""Deep Learning for X-ray Image to Text Generation"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23168.pdf
Paper URL: https://www.ijtsrd.com/engineering/information-technology/23168/deep-learning-for-x-ray-image-to-text-generation/mahima-chaddha
Object tracking with SURF: ARM-Based platform ImplementationEditor IJCATR
Several algorithms for object tracking, are developed, but our method is slightly different, it’s about how to adapt and implement such algorithms on mobile platform.
We started our work by studying and analyzing feature matching algorithms, to highlight the most appropriate implementation technique for our case.
In this paper, we propose a technique of implementation of the algorithm SURF (Speeded Up Robust Features), for purposes of recognition and object tracking in real time. This is achieved by the realization of an application on a mobile platform such a Raspberry pi, when we can select an image containing the object to be tracked, in the scene captured by the live camera pi. Our algorithm calculates the SURF descriptor for the two images to detect the similarity therebetween, and then matching between similar objects. In the second level, we extend our algorithm to achieve a tracking in real time, all that must respect raspberry pi performances. So, the first thing is setting up all libraries that the raspberry pi need, then adapt the algorithm with card’s performances. This paper presents experimental results on a set of evaluation images as well as images obtained in real time.
The 2020 ski season is just around the corner, but with COVID-19 limiting access to your favorite ski area, what is an avid skier to do? Backcountry skiing promises no lines, a limited number of people, and the allure of carving turns through fresh snow, but before you head out, it is essential to have a solid understanding of what it takes to get out there responsibly, sustainably, and safely.
Join Tahoe Silicon Mountain, a local network of entrepreneurs and professionals, today, November 9th, for a panel discussion with a team of backcountry ski experts to help educate you on the essential things you need to know before you strap on your skins and head out. Some of the key topics we will cover:
• Gear: What you really need to get started
• Avalanche Safety 101 and Local AVI I certification resources
• Lake Tahoe backcountry spots
Our panelists will Include:
Andy Rathbun, Administrator and Moderator for San Francisco Backcountry Skiers
David Reichel, Executive Director of the Sierra Avalanche Center
Emily Hargraves, Chief Executive Babe of Backcountry Babes
Vans used for getting outdoors range from simple vans to significant upgrades in 4 x 4 adventure vans, almost tiny homes. Nick Polinko provides insights he gained in making his enhanced van.
ahoe Silicon Mountain, a local network of entrepreneurs and professionals, is pleased to welcome Dave Sick to present on Raising Startup Capital in Tahoe.
Come hear first hand the stories and lessons learned from someone who has spent the last three years raising capital and starting and growing a company. Dave also brings a unique perspective of someone who has been on both sides of the table, as previous roles include analyst at a VC fund, small time angel investor, and startup founder. His presentation will cover what you need to be ready to start pitching and how to find capital for your startup.
Dave Sick is the Co-Founder and CTO at Stomp Sessions and a Truckee local. His resume touts Silicon Valley Startups, Marketing and Technology at Booth Creek (acquired by Vail), and Product Management at Clear Capital.
Please join us at Mountain Minds Monday on Monday, May 13th from 6-8pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad are available and we use a pay-what-you-can model ($5 minimum). Before and after the presentation, there will be time for networking.
This month’s event is sponsored by Holland & Hart LLP and Molsby & Bordner, LLP.
The event will also be available on YouTube as a livestream and after the event: bit.ly/YouTubeTSM
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
Tahoe Silicon Mountain, a local network of entrepreneurs and professionals, is pleased to welcome Pamela Hurt Hobday and Colleen Dalton to present the key takeaways from the recent Mountain Ventures Summit held in Mammoth, California.
The Summit hosted over 41 mountain town communities aspiring to diversify their towns and grow their middle class and economy with year-round sustainable startups. Hobday will discuss how the 41 mountain towns are taking action to improve their communities. Dalton, who was the keynote speaker at the event, will discuss protecting and measuring the quality of life in mountain towns and Truckee specifically.
Dalton is the Brand Communications Director at the Truckee Chamber, and Hobday, who will be representing Truckee Tomorrow, a Truckee Chamber initiative, is CEO of Pamela Hurt Associates.
Please join us at Mountain Minds Monday on Monday April 8th from 6-8pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad are available and we use a pay-what-you-can model ($5 minimum). Before and after the presentation, there will be time for networking.
The event will also be available on YouTube as a livestream and after the event: bit.ly/YouTubeTSM
This month’s event is sponsored by Holland & Hart LLP and Molsby & Bordner, LLP.
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
Tahoe Silicon Mountain, a local network of entrepreneurs and professionals, is pleased to welcome Dr. John Limansky, a board-certified physician in internal medicine, who will discuss improving your health and your business’s profitability through biohacking and nutrition.
The loss of productivity and cost of healthcare can be a significant burden for families, small businesses, startups, and corporations alike. Combining biohacking techniques like low carb or ketogenic diets, improved sleep habits, stress reduction, exercise, photo bio-modulation, cold and heat stress, and more can positively affect health, productivity, longevity, and well-being.
This talk will be geared towards both individuals and business owners who are interested in improving health, combatting the effects of a modern western diet and lifestyle, re-gaining productivity, and working at optimal levels.
You can learn more about Dr. Limansky, his writing, and his podcast, KetoHacking MD, on his website: https://johnlimanskymd.com.
Please join us at Mountain Minds Monday on Monday March 11th from 6-8pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad are available and we use a pay-what-you-can model ($5 minimum). Before and after the presentation, there will be time for networking.
The event will also be available on YouTube as a livestream and after the event: bit.ly/YouTubeTSM
This month’s event is sponsored by Holland & Hart LLP and Molsby & Bordner, LLP.
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
https://www.tahoesiliconmountain.com/
Tahoe Silicon Mountain, a local network of entrepreneurs and professionals, is pleased to welcome Will Richardson to discuss winter wildlife adaptations in his presentation: “Hibernate, Hoof It, or Hang Tough: Winter Wildlife Survival.”
Richardson will discuss how the different animals of the Tahoe ecosystem combat the elements to make it through the winter. He will delve into where animals go and what they do to survive the cold and the snow to be able to emerge again in the spring.
Richardson is the Co-founder and Executive Director for the Tahoe Institute for Natural Science and received his Ph.D. in Ecology, Evolution, and Conservation Biology from the University of Nevada, Reno, studying bird communities in Sierra Nevada aspen habitats.
Please join us at Mountain Minds Monday on Monday February 11th from 6-8pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad are available and we use a pay-what-you-can model ($5 minimum). Before and after the presentation, there will be time for networking.
The event will also be available on YouTube as a livestream and after the event: bit.ly/YouTubeTSM
This month’s event is sponsored by Holland & Hart LLP and Molsby & Bordner, LLP.
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
https://www.tahoesiliconmountain.com/
Tahoe Silicon Mountain, a local network of entrepreneurs and professionals, is pleased to welcome attorney Dick Schulze of Holland & Hart to present at Mountain Minds Monday: “Ahead of Her Time: True Stories About Women Tech Stars.”
Schulze will discuss how women who were inventors with patents were many times unrecognized and unrewarded.
Schulze will also discuss some of the frustrations and triumphs of other inventors, and will give the listener some ideas about what to do with their own invention.
Schulze is an intellectual property attorney with Holland & Hart, LLP specializing in high-tech electronic and other inventions as well as copyright and trademark law.
Please join us at Mountain Minds Monday on Monday, January 14th from 6-8pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad are available and we use a pay-what-you-can model ($5 minimum).
Before and after the presentation, there will be time for networking.
The event will also be available on YouTube as a livestream and after the event: bit.ly/YouTubeTSM
This month’s event is sponsored by Holland & Hart, LLP and Molsby & Bordner, LLP.
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
Tahoe Silicon Mountain, a local network of entrepreneurs and professionals, is pleased to welcome Dave Nickens to present at Mountain Minds Monday: “The Future of Shopping: Virtual, Mixed, and Augmented Reality”
Billions of dollars are being invested in virtual reality (VR), augmented reality (RM), and mixed reality (MR), which are set to disrupt both traditional online and offline shopping experiences. Come learn what each of these technologies are, how they can be used, and how recent advances in Apple and Google smartphone technology, when combined with VR, AR, and MR can enhance the shopping experience.
Dave Nickens, Head of Emerging Technology at Ferguson Ventures, who plays a lead role in bringing immersive eCommerce initiatives to Ferguson, will lead a discussion about recent advances, lessons learned, and the future of immersive commerce, including technologies like MR-infused eyewear.
Mountain Minds Monday will be held on Monday, November 12th from 6-8 pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad are available and we use a pay-what-you-can model ($5 minimum). Before and after the presentation, there will be time for networking.
The event will also be livestreamed and available online as it happens on YouTube: bit.ly/YouTubeTSM
This month’s event is sponsored by Holland & Hart LLP and Molsby & Bordner, LLP.
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
Tahoe Silicon Mountain, a local network of entrepreneurs and professionals, is pleased to welcome Neil Lareau to present at Mountain Minds Monday: “Why Tahoe Gets So Much Wildfire Smoke and How We Can Predict It”
Come learn from a physicist why we’ve had so many smoky days in Tahoe and how cutting-edge remote sensors provide new perspectives about wildfires that can help us advance our ability to predict their impacts on society.
Neil Lareau, Assistant Professor of physics at the University of Nevada, Reno, will explain the inner workings of destructive and extreme fire behaviors like fire tornadoes, 130+ mph winds, and pyrocumulus clouds that can reach 40,000 feet into the atmosphere.
Mountain Minds Monday will be held on Monday, October 8th from 6-8 pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad are available and we use a pay-what-you-can model ($5 minimum).
Before and after the presentation, there will be time for networking.
The event will also be livestreamed and available online as it happens on YouTube: bit.ly/YouTubeTSM
This month’s event is sponsored by Holland & Hart LLP, Molsby & Bordner, LLP, Mountain Workspace, and Heads Up Health.
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
Tahoe Silicon Mountain, a network of entrepreneurs and professionals who live and work in the Tahoe-Truckee area, is pleased to welcome Mary L. Gorden to present at Mountain Minds Monday: “The History of Computing Through the Eyes of One Woman's Career”
Mary L. Gorden, author of "Life Without Ceilings: A Woman’s Career in Computers" will give us an insider’s view of the role women played in computing throughout her 35-year career in the field.
Using events from her career, Gorden will describe the change in attitude towards both computers and women in technology, how some new approaches today are really old ideas using newer technology, and how and why the numbers of women in computing have changed over time.
Mountain Minds Monday will be held on Monday, August 13th from 6-8 pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad are available and we use a pay-what-you-can model ($5 minimum). Before and after the presentation, there will be time for networking.
The event will also be livestreamed and available online as it happens on YouTube: bit.ly/YouTubeTSM
This month’s event is sponsored by Holland & Hart LLP, Molsby & Bordner, LLP, Mountain Workspace, and Heads Up Health.
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
The Science of Low Carb Diets: Reversing Diabetes and Enhancing Sports Perfor...Tahoe Silicon Mountain
Tahoe Silicon Mountain, a network of entrepreneurs and professionals who live and work in the Tahoe-Truckee area, is pleased to welcome Stephen Phinney, MD, PhD to present at Mountain Minds Monday: The science of low carb diets: reversing diabetes and enhancing sports performance
While low carbohydrate and ketogenic diets have recently gained popularity, problems with proper formulation and adherence have overshadowed the scientifically-supported improvements shown for both health and sports performance.
Dr. Stephen Phinney, MD, PhD, co-founder and Chief Medical Officer at Virta Health, will explain how when well-formulated ketogenic diets are combined with virtual continuous care, compliance is high and the risks and expense associated with type 2 diabetes can be reduced.
He’ll also discuss how the research supports the use of the ketogenic diet for ultra-endurance competitive athletes who do not thrive on the traditional carbohydrate-loading approach to the sport.
Dr. Phinney has spent 40 years studying diet and exercise, has published over 80 papers and 4 books. He received his MD from Stanford University, PhD in Nutritional Biochemistry from MIT, and did post-doctoral training at the University of Vermont and at Harvard.
Mountain Minds Monday will be held on Monday, July 9th from 6-8 pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad is available and we use a pay-what-you-can model ($5 minimum). Before and after the presentation, there will be time for networking.
The event will also be livestreamed and available online as it happens on YouTube: bit.ly/YouTubeTSM
This month’s event is sponsored by New Leaders, Holland & Hart LLP, Molsby & Bordner, LLP, and Mountain Workspace.
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
Tahoe Silicon Mountain, a network of entrepreneurs and professionals who live and work in the Tahoe-Truckee area, is pleased to welcome Allison Clift-Jennings, Adam Kiefer, and Aaron Sturm to discuss their experiences participating in startup accelerator programs.
It’s not easy to get a startup off the ground and highly competitive startup accelerator programs like Techstars and Y-Combinator (whose graduates include Airbnb and Dropbox) have become a way for startups to grow a network, get advice, and receive investment to catalyze their growth.
Join us for a moderated panel discussion with three local founders, Allison Clift-Jennings, CEO of Filament, Adam Kiefer, CEO and Co-founder of Talage, and Aaron Strum, Head of Business Development for StreamLoan, each of whom has been through two accelerator programs.
Targeting their discussion to both those generally interested in startups and startup founders ready to explore applying to an accelerator, they’ll discuss the pros and cons of startup accelerators, how you get into these highly competitive programs, and what startups can expect to get out of them during these 3-month intensives.
Mountain Minds Monday will be held on Monday, June 11th from 6-8 pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad are available and we use a pay-what-you-can model ($5 minimum). Before and after the panel discussion, there will be time for networking.
The event will also be livestreamed and available online as it happens on YouTube: bit.ly/YouTubeTSM
This month’s event is sponsored by New Leaders, Holland & Hart LLP, The Lift, Molsby & Bordner, LLP, and Mountain Workspace.
You can find us at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
Tahoe Silicon Mountain, a network of entrepreneurs and professionals who live and work in the Tahoe-Truckee area, is pleased to welcome Maria Tran to present at Mountain Minds Monday: “Running A Global Nonprofit from a Mountain Town”
Haunted by the photo of the body of a 3-year-old refugee washed up on a beach in Greece, Truckee’s Maria Tran decided to do something about it.
First as a volunteer, and next as co-founder of Sea of Solidarity, a nonprofit that supports grassroots humanitarian and educational projects in Greece and Turkey, Tran has taken advantage of technology to save lives, organize relief efforts, raise awareness, and to galvanize people from around the world (including Truckee) to volunteer.
Come hear Tran’s story of running a highly responsive global nonprofit from Truckee, including how she began as a product manager in Silicon Valley and transitioned to Truckee, how she’s been able to involve local students who will be traveling to Greece and how forming partnerships with local entrepreneurs can strengthen Sea of Solidarity’s efforts.
Mountain Minds Monday will be held on Monday, March 12th from 6-8 pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad is available and we use a pay-what-you-can model ($5 minimum). Before and after the presentation, there will be time for networking.
The event will also be livestreamed and available online as it happens on YouTube: bit.ly/YouTubeTSM
This month’s event is sponsored by New Leaders, Holland & Hart LLP, Molsby & Bordner, LLP, and Mountain Workspace.
You can find us on LinkedIn and Facebook and at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
Tahoe Silicon Mountain, a network of entrepreneurs and professionals who live and work in the Tahoe-Truckee area, is pleased to welcome Dr. Kelly Gleason and Meghan Collins to present at Mountain Minds Monday: “Why Snow Scientists Study Fire Effects and How You Can Help”
More than 25 million California residents get their water from the Sierra Nevada, making it vital to understand how the snow will melt each season, based on factors like the severity of the previous season’s wildfires or drought.
Dr. Kelly Gleason, a Postdoctoral Fellow in Hydrology at Desert Research Institute (DRI), will share her work on how our changing climate and recent extreme wildfire season could shorten your spring skiing.
Then, learn how you can help deepen our understanding of snow through DRI’s new citizen scientist program, Stories in the Snow - which is the first of its kind to engage citizens to collect snow crystal data. Meghan Collins, who is part of DRI's STEM Outreach Team, will explain how important just a few minutes of our time on a powder day can make a big difference in helping researchers fill the knowledge gaps around how snowflakes form.
Learn more about the DRI’s citizen scientist program at: http://www.dri.edu/stories-in-the-snow
Mountain Minds Monday will be held on Monday, November 13th from 6-8 pm at Pizza on the Hill, in Tahoe Donner located at 11509 Northwoods Blvd., Truckee. Pizza and salad is available and we use a Pay-What-You-Want model if you’d like to have dinner ($5 minimum). Before and after the presentation, there will be time for networking.
The event will also be livestreamed and available online as it happens on YouTube: bit.ly/YouTubeTSM
This month’s event is sponsored by New Leaders, Holland & Hart LLP, Molsby & Bordner, LLP and The Lift.
You can find us on LinkedIn and Facebook and at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
How “Civic Technologies” Can Create Happy Citizens and Improve Local GovernmentTahoe Silicon Mountain
http://www.tahoesiliconmountain.com/
Tahoe Silicon Mountain, a network of entrepreneurs and professionals who live and work in the Tahoe-Truckee area, is pleased to welcome Kevin Lyons to present at Mountain Minds Monday: “How Civic Technologies Can Create Happy Citizens and Improve Local Government.”
At a time when citizens’ satisfaction with national and state government is low, there is a need for innovation at the local level to better serve citizens.
Kevin Lyons, serial entrepreneur and a longtime “good governance geek,” is Co-Founder and CEO of Governance Sciences Group, the creator of FlashVote, which helps governments get rapid feedback from busy citizens.
In this interactive discussion, Lyons will present the science of good government and discuss how and why government can end up off track. Learn how the future is bright for fixing these problems with technology all while saving money, providing more value and making citizens happier.
You can learn more about Lyons’ company here: www.flashvote.com
Mountain Minds Monday will be on Monday, July 10th, 6-8 pm at Pizza on the Hill, in Tahoe Donner at 11509 Northwoods Blvd., Truckee. A $5 fee includes pizza and salad. Before and after the presentation, there will be time for networking.
The event will also be livestreamed and available online as it happens on YouTube: bit.ly/YouTubeTSM
This month’s event is sponsored by New Leaders, Holland & Hart LLP, and The Lift.
You can find us on LinkedIn and Facebook and at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
B Corps: Using Business as a Force for Good™ presented by Maiya HollidayTahoe Silicon Mountain
Tahoe Silicon Mountain, a network of entrepreneurs and professionals who live and work in the Tahoe-Truckee area, is pleased to welcome Maiya Holliday and Marie Koesnodihardjo to present: “B Corps: Using Business as a Force for Good™” at the Mountain Minds Monday event.
Many businesses already operate using a triple bottom line framework, but consumers don’t necessarily see companies’ environmental and sustainability initiatives as authentic. Come learn how the B Corp certification defines and upholds standards for environmental and social accountability that creates benefit for stakeholders and shareholders and how your company can become a certified B Corp.
Maiya Holliday, Founder and Technical Lead at Mangrove Web Development, and Marie Koesnodihardjo, Project Manager and B Keeper at Mangrove Web Development, will talk about how your business, whether large or small, can join the growing community of more than 1,600 Certified B Corps from 42 countries and over 120 industries to redefine success in business.
You can learn more about Holliday and Koesnodihardjo here: mangrove-web.com
Mountain Minds Monday will be on Monday, June 12th, 6-8 pm at Pizza on the Hill, in Tahoe Donner at 11509 Northwoods Blvd., Truckee. A $5 fee includes pizza and salad. Before and after the presentation, there will be time for networking.
The event will also be livestreamed and available online as it happens on YouTube: bit.ly/YouTubeTSM
This month’s event is sponsored by New Leaders, Holland & Hart LLP, and The Lift.
You can find us on LinkedIn and Facebook and at TahoeSiliconMountain.com or sign up for email meeting announcements here: http://bit.ly/TSMEmail
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
Self-Flying Drones: On a Mission to Navigate Dark, Dangerous and Unknown Worlds
1.
2. Self-Flying Drones: On a mission
to navigate Dark, Dangerous and Unknown Worlds
Christos Papachristos
Autonomous Robots Lab, University of Nevada, Reno
3. Broader Vision
´ In all non-too-distant visions of the future,
robots are part of everyday lives, fulfilling the
roles of humanity’s need for comfortable
transportation, everyday safety and security, a
tireless and reliable workforce, or even that of
a convenient company. The robots of such a
future –from single appliance to entire cities–
can operate on their own.
´ Robotics can promote sustainable and scalable
growth, even out societal disparity, improve our
quality of life, accelerate scientific progress, and
more.
´ To reach this scale, a concrete baseline is
necessary to provide the foundations of high-
level perception, navigation, task-handling,
reasoning, etc.
´ Autonomy is the key. The absolute baseline is
Robust Perception and Autonomous Planning.
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
4. Motivation
´ On one hand Aerial Robots are exceptional
candidates for jobs that require going to
remote locations to inspect, map, and monitor
their environment. These locations can be:
´ Particularly difficult to reach and/or GPS-denied.
´ Engulfed in complete darkness or White-washed.
´ Hazy due to atmospheric conditions or dust
within enclosed spaces.
´ Hazardous for human health.
´ Autonomous Aerial Robotic Operation in
GPS-denied Degraded Visual Environments
´ Indicative Application domains:
´ Nuclear Site Decommissioning
´ Remote Infrastructure Inspection
´ Oil & Gas Industry Inspection
´ Surveillance, Security Monitoring
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
5. Putting the Pieces together
´ Robotic Autonomy :
The ability to operate without the need for human action and reasoning and make own choices.
´ Generate moves
sequence from A to B.
´ Objectives: Exploration,
Inspection, …
´ Rules: Collision-free,
Power-limitations, …
´ Optimize
response.
´ Guarantee
constraints.
´ Robot
Configuration.
´ Sensor Suite.
´ Processing
Components.
´ Multi-modal Perception:
Visual, Inertial, LIDAR,
Thermal, …
´ Robust State Estimation:
GPS-denied, DVE(s), …
A baseline for Autonomous Mobile Robots
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
6. Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
Putting the Pieces together
´ Starting off with the basics for a simple yet fully-autonomous aerial robot:
7. Visual – Inertial SLAM
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ The Simultaneous Localization & Mapping problem
Vision-based feature detection and tracking
Detect – Track – Recover Structure from Motion
´ Formulate as Estimation process with Bayesian Reasoning.
´ Correlate robot pose Uncertainty to measurement
Uncertainty (landmark 3D positions).
´ Information Fusion via Joint Distribution of processes that
contain Uncertainty.
8. Visual – Inertial SLAM
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Visual-only SFM Limitations
2D-projective transformation introduces problem of scale
Inertial (IMU) data have absolute scale
´ Use an Extended Kalman Filter – Prediction Step
9. Visual – Inertial SLAM
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Visual-only SFM Limitations
2D-projective transformation introduces problem of scale
Inertial (IMU) data have absolute scale
´ Use an Extended Kalman Filter – Update Step
Visual-Inertial Localization – Altogether:
´ System Model: Propagation of Estimate &
Uncertainty based on Rigid Body model and
accelerometer & gyroscope data.
´ Measurement Model: Correction based on
landmark-states observation (camera-based
feature detection).
10. Visual – Inertial SLAM
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Visual – Inertial Localization and Mapping
Using a Stereo Camera
´ Reliable stereo camera model gives
better landmark estimation statistics.
´ Improved 3D pose estimation.
´ Consistent stereo depth map.
´ “Dense” Reconstruction / Mapping
Left
Camera
Right
Camera
11. Volumetric Mapping
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Visual-Inertial Localization and Mapping & Dense Reconstruction
From Dense to Volumetric Mapping
Voxel-grid from PointCloud (octomap)
´ Volumetric representation of the
known environment.
´ Makes distinction between occupied
& free voxels based on a probabilistic
hit/miss model of a depth sensor.
´ Efficient representation in memory
( octree structure, nodes store
“occupied” probability ).
´ Fast node (voxel) lookup (usually
hash-table based) given its 3D
coordinates.
12. Volumetric Mapping
´ Octomap(s)
Volumetric Mapping & Robotic Autonomy
Ray collision checks for landmark visibility
l1
l2 l3
l4
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
Fast node-lookup benefits ray-checking
´ Ray-casting / Ray-checking is the
process of checking along a 3D line
segment (ray) if occupied, free, or
unmapped voxels are crossed.
´ Checking if a transition from initial 3D
configuration to a desired one
(waypoint) will encounter an
obstacle.
´ Checking if a 3D landmark lies in
Line-of-Sight or “occluded”.
13. Path-Planning
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Core Path-planning Principles :
Random Sampling
Expanding Random Trees in the known (mapped) and free configuration space.
´ Only Collision-free transitions are
permitted for every segment.
´ Collision-free navigation along path.
14. Path-Planning
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Core Path-planning Principles :
Receding-Horizon Strategy
´ A finite number of path-planning moves (e.g. the first segment only) is performed.
´ Real-time feedback from mapping updates the environment knowledge. Based on this
updated state, path-planning is re-evaluated.
´ The first moves is performed again, with each iteration followed by a new map update.
15. Autonomy & Active Perception
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ The Objective:
Explore a location while mapping with consistency.
Given a bounded volume 𝑉"
, find a collision free path 𝜎 starting at an initial
configuration 𝜉%&%' ∈ Ξthat leads to identifying the free and occupied parts 𝑉*+,,
"
and 𝑉-..
"
when being executed, such that there does not exist any collision free
configuration from which any piece of 𝑉"
{𝑉*+,,
"
, 𝑉-..
"
} could be perceived.
Problem 1: Volumetric Exploration
Given a 𝑉1
⊂ 𝑉"
, find a collision free path 𝜎1
starting at an initial configuration 𝜉3 ∈ Ξ
and ending in a configuration 𝜉*%&45 ∈ Ξ that aims to improve the robot’s localization
and mapping confidence by following paths of optimized expected robot pose and
tracked landmarks covariance.
Problem 2: Belief Uncertainty-aware planningCombined Problem
The overall problem is that of exploring an unknown bounded 3D volume 𝑉"
⊂ ℝ7
, while
aiming to minimize the localization and mapping uncertainty as evaluated through a
metric over the robot pose and landmarks probabilistic belief.
Problem Definition
16. Autonomy & Active Perception
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Objective 1: Volumetric Exploration
Receding-Horizon Exploration & Mapping Path-planner (rhemplanner)
Two-level Path-planning
paradigm:
´ Addresses the combined
problem in a hierarchical
approach.
´ At every iteration, a finite
depth random tree is
spanned. Each vertex is
annotated with a collected
Information Gain – a metric of
how much new space is
going to be explored.
Planning Layer 1:
Volumetric Exploration
17. Autonomy & Active Perception
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Objective 1: Volumetric Exploration
Receding-Horizon Exploration & Mapping Path-planner (rhemplanner)
´ Tree-based exploration: At
every iteration, a finite depth
random tree is spanned.
Each vertex is annotated with
the collected Information
Gain – a metric of how much
new space is going to be
explored.
´ Within it, evaluation regarding
the path that overall leads to
the highest information gain is
conducted. This corresponds
to the best path for the given
iteration (a sequence of next-
best-views as sampled).
´ Receding Horizon: For the
extracted best path, only
the first viewpoint is
actually executed.
´ The system moves to it,
map is updated, process
is repeated.
Executed
Step
18. Autonomy & Active Perception
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Objective 1: Volumetric Exploration
Receding-Horizon Exploration & Mapping Path-planner (rhemplanner)
´ Probabilistic Re-observation term: Maximize newly explored space and try to re-observe
the parts where confidence whether they are occupied is low.
19. Autonomy & Active Perception
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Objective 2: Uncertainty – Aware Path-planning
Receding-Horizon Exploration & Mapping Path-planner (rhemplanner)
Two-level Path-planning paradigm:
´ Hierarchical structure:
´ Given an exploration 1st view-
point, another 2nd layer random
tree is spanned locally
“around” that vertex. Each
possible path leading to the
end-configuration is annotated
with a Belief Gain – a metric of
how much the robot belief has
improved / deteriorated.
´ The mechanism to propagate
robot’s belief has to be
established.
Planning Layer 2:
Uncertainty-Optimization
20. Autonomy & Active Perception
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Objective 2: Uncertainty – Aware Path-planning
Receding-Horizon Exploration & Mapping Path-planner (rhemplanner)
´ Exploit the EKF pipeline used for SLAM to propagate belief.
´ Propagate State
and Uncertainty
along all paths.
´ Assume closed-loop dynamics, simulate inertial measurements.
Predict
Step
21. ´ Exploit the EKF pipeline used for SLAM to propagate belief.
´ Propagate State
and Uncertainty
along all paths.
´ Use octomap representation to predict
landmark visibility / occlusion.
´ Perform virtual updates for all landmarks
expected to be seen.
Autonomy & Active Perception
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Objective 2: Uncertainty – Aware Path-planning
Receding-Horizon Exploration & Mapping Path-planner (rhemplanner)
Update
Step
l1
l2
l3
l4
22. Autonomy & Active Perception
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Objective 2: Uncertainty – Aware Path-planning
Receding-Horizon Exploration & Mapping Path-planner (rhemplanner)
´ Finally, compute the propagated covariance matrix for every path:
´ The D-optimality metric is a measure of how “small” the corresponding ellipsoid is:
´ Choose the path that minimizes the D-optimality
metric – i.e. minimizes the Uncertainty on arrival.
´ This path might turn out to be the original straight
segment – Optimum is only selected out of a
finite number of randomly sampled trajectories.
23. Autonomy & Active Perception
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Receding-Horizon Uncertainty-aware Exploration & Mapping Path-planner (rhemplanner)
24. Autonomy & Active Perception
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Receding-Horizon Uncertainty-aware Exploration & Mapping Path-planner (rhemplanner)
26. Degraded Visual Environments
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Uncertainty-Aware Exploration & Mapping
Tying back to the original motivation
´ Particularly for DVEs, pure volumetric exploration is
not sufficient.
´ The selected viewpoints and their sequence will
heavily influence the localization of the robot.
´ A 1st generation of Multi-Modal sensor fusion for
GPS-denied localization and mapping in DVEs.
NIR Cameras
& IR LED(s)
Time-of-Flight
3D Camera
IMU
27. Degraded Visual Environments
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Uncertainty-Aware Exploration & Mapping
Tying back to the original motivation
´ A 1st generation of Multi-Modal sensor fusion for GPS-denied localization and mapping in DVEs.
´ Same Active Perception approach for reliable autonomy subject to the challenges of DVEs.
NIR Cameras
& IR LED(s)
Time-of-Flight
3D Camera
IMU
28. Degraded Visual Environments
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Multi-Modal Mapping Unit
Tightly-integrated Multi-Modal sensor (featuring Hardware-synchronization, Expansions, …)
´ Inertial Sensors (accelerometers, gyroscopes)
´ Vision (synchronized with flashing LEDs)
´ Depth Cameras (Time-of-Flight)
´ GPS integration-ready
´ Support for multi-Camera setups
29. Degraded Visual Environments
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Field Experiments
The “real” test – A driving force for improvement
´ Autonomous Robotic Navigation, Exploration, Inspection and Mapping in GPS-denied DVEs.
´ Technology developed in-house. Demonstrated in Field Experiments.
´ The 1st generation of Multi-Modal
sensor fusion:
´ Visual-Inertial / Depth – odometry
loosely-coupled via EKF.
30. Degraded Visual Environments
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Multi-Modal Mapping Unit
Tightly-integrated Multi-Modal sensor (featuring Hardware-synchronization, Expansions, …)
31. Nuclearized Robotics
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Field Experiments
The “real” test – A driving force for improvement
Nuclearized Robots
32. Nuclearized Robotics
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Motivation
The Nuclear Cleanup Mission
´ Nuclear facility decommissioning.
´ Soil and water cleanup.
´ Liquid radioactive waste processing & disposition.
´ Solid radioactive waste treatment, storage and disposal.
´ Nuclear materials and spent nuclear fuel management.
Figure from DOE – EM
33. Nuclearized Robotics
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Motivation
DOE – EM Facilities Characterization
´ Flying & roving robots to help characterize DOE – EM facilities.
Goal set for demonstration of developed technologies in nuclear analog facilities of DOE – EM.
´ Identification and Semantic Classification of tanks, pipes, and other important structures to
intelligently focus the robot exploration and inspection tasks.
´ Radiation, Chemical, and Heat spatial maps are fused with 3D models of the environment.
´ Integrated Planning & Multi-Modal perception for comprehensive mapping of nuclear facilities,
Active Perception to improve (while benefiting from) radiation, chemical, heat estimation.
34. Nuclearized Robotics
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Robotic Detection of Ionizing Radiation
Target Platform: Autonomous Micro Aerial Vehicles
´ Detection of Gamma Radiation – common need
and requirement of the decommissioning efforts.
Key technologies:
´ Miniature CeBr3, CsI, NaI scintillators with built-in
temperature compensated bias generator and
pre-amplifier alongside a Silicon Photomultiplier
tube.
´ Miniature solid-state low voltage detectors.
´ Gamma cameras (heavy for aerial robots).
35. Nuclearized Robotics
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Robotic Detection of Ionizing Radiation
Gamma Radiation Detection
´ Sensor calibration is required too:
´ Radiation detectors can present significant
polarity characteristics. Calibration requires
exhaustive tests for different sensor orientations.
´ Differential installment of two gamma detectors
will potentially enhance source localization.
´ Integration of spectroscopy through relevant
algorithms and a multi-channel analyzer.
Calibration against known characterized
sources allows estimation of detected gamma
photon energy.
´ Estimation / Characterization of types of sources
contributing to a region’s radioactivity.
´ “Hunt” for specific expected radioactive source
types.
36. Nuclearized Robotics
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Robotic Detection of Radiation
Other Radiation types:
´ Neutron Detection is relevant with homeland
security and industrial monitoring (e.g.
detection of nuclear weapons, personnel
monitoring, water content in soil).
´ Gas-filled (e.g. He-3), Scintillation, Solid-State.
´ Alpha Detection is very challenging. Alpha
particles are the heaviest and highly charged,
they quickly give up their energy to any
medium they pass.
´ Special detection methods are required, gas-
filled detector [ZnS(Ag)] combined with
Aluminized Mylar film.
´ Requires contact & robotic manipulation.
37. Nuclearized Robotics
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Robotic Detection of Radiation
Autonomous Exploration & Mapping Aerial Robot for DVE and Nuclear Sites
Gamma Detector
Multi-Modal Perception Unit Scintillation Detector(s) Solid-State Detector(s)
38. Nuclearized Robotics
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Robotic Detection of Radiation
Autonomous Exploration & Mapping Aerial Robot for DVE and Nuclear Sites
39.
40. Further Research & Applications
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Robotic Detection of Change
´ Perform real-time change detection.
´ Expand to efficient 3D-to-3D change
detection approaches.
´ Incorporate change-driven “curiosity” in
planning algorithms.
41. Further Research & Applications
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Curious Robots
´ Employ a human-paradigm for interest: Collect more meaningful data without
necessarily having any explicit mission objective.
´ Ability to focus perceptual attention towards regions that have “Visual Saliency”
42. Further Research & Applications
Christos Papachristos, Autonomous Robots Lab, University of Nevada, Reno
´ Augmented – Reality Robotics
´ Provide Real-Time feedback of data annotated with Mission-Relevant information.
´ Take the actual flying away from the human, but still maintain the ability to redirect the
robot’s attention towards areas of interest.