The document describes the design and fabrication of a ground surveillance robot called SPyDER. Some key points:
1. SPyDER has a wireless RF control system, 2-axis camera mount, wireless video transmission, and speed control of DC motors using a discrete PID controller for easy and precise movement via joystick.
2. The mechanical assembly includes the robot base along with pan-tilt camera mount. The hardware design has onboard and control station circuits interfaced with microcontrollers.
3. Firmware was developed in C for microcontroller programming and Visual Basic for the GUI. A discrete PID controller was implemented to control motor speed through PWM based on encoder feedback.
The LayerZero Power Systems ePODs: Type-S contains Two Transformers, a Static Transfer Switch, and the SafePanel Panel Board for Subfeed Distribution. Designed with an emphasis on operator safety, ePODs: Type-S is a reliable, quality-built PDU.
CETPA INFOTECH PVT LTD is one of the IT education and training service provider brands of India that is preferably working in 3 most important domains. It includes IT Training services, software and embedded product development and consulting services.
CETPA INFOTECH PVT LTD is one of the IT education and training service provider brands of India that is preferably working in 3 most important domains. It includes IT Training services, software and embedded product development and consulting services.
http://www.cetpainfotech.com
The LayerZero Power Systems ePODs: Type-S contains Two Transformers, a Static Transfer Switch, and the SafePanel Panel Board for Subfeed Distribution. Designed with an emphasis on operator safety, ePODs: Type-S is a reliable, quality-built PDU.
CETPA INFOTECH PVT LTD is one of the IT education and training service provider brands of India that is preferably working in 3 most important domains. It includes IT Training services, software and embedded product development and consulting services.
CETPA INFOTECH PVT LTD is one of the IT education and training service provider brands of India that is preferably working in 3 most important domains. It includes IT Training services, software and embedded product development and consulting services.
http://www.cetpainfotech.com
Tachometer using AT89S52 microcontroller with motor controlSushil Mishra
Tachometer using AT89S52 microcontroller with motor control using H bridge method
We , in this project are measuring the RPM of a motor using an IR sensor.
The motor speed and direction is made variable by use of a H-bridge method.
RPM is shown on LCD display for the two directions.
Camera Movement Control using PID Controller in LabVIEWijtsrd
The aim of this system is to show how position of the dc motor can be controlled by using PID algorithm in LabVIEW for camera movement. Arduino microcontroller board is used to control the DC motor. L298N dual H Bridge motor driver is used to drive the DC motor and to execute the pulse width modulation PWM signal. Proportional Integral Derivative PID is the most common control algorithm used in industrial applications and other control system. DC motor will be interfaced with LabVIEW using an Arduino Uno microcontroller. The position of the DC motor will be set by creating a Graphic User Interface GUI in LabVIEW. LabVIEW GUI sends serial command to the microcontroller for driving PWM pins of the DC motor . DC motor will move by the user in LabVIEW for position control. The output is sent back to the PID controller in Uno microcontroller. PID compares the actual position of the DC motor with the desired position. In this system, PID controller is used to reduce the error and rotate the motor to the set point value for the camera movement control. Than Myint Kyi | Kyaw Zin Latt "Camera Movement Control using PID Controller in LabVIEW" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26397.pdfPaper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/26397/camera-movement-control-using-pid-controller-in-labview/than-myint-kyi
Codemotion Rome 2015 - Building a drone from scratch with spare parts is a challenging business. To accomplish this journey, a Linux embedded stability control system is developed entirely from 0.This is a journey starting from the hardware choosing (a home WIFI router), to a stable and real flight. Unconventional implementations are one of the main topic, like using WiFi as communication between drone and pilot, HTML5 and COMET to show telemetry from the router web server, and implementing a entirely new protocol based on 802.11 Beacon Frames to prevent deauthentication attacks.
Final Year Engineering Project Seminar
For more information, check out my papers online:
Command controlled robot:
http://www.ijtre.com/manuscript/2014010976.pdf
Self controlled robot:
http://www.ijtre.com/manuscript/2014011008.pdf
Gesture controlled robot:
http://www.ijtre.com/manuscript/2014011107.pdf
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The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
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Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
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Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
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As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
3. Project Team
Imran Zahid
Faiza Waheed
Asst. Prof. Cdr (R) Riaz Mahmud TI (M)
Lect. Engr. Farhan Khan
Department of Electronics & Power Engineering
Pakistan Navy Engineering College (PNEC)
National University of Sciences and Technology (NUST)
3
4. Scheme of Presentation
• Aims & Objectives
• Scope of Project
• Robot Mechanical Assembly
• Hardware Design
• Firmware Design
• PID results and analysis
• System Limitations
• Practical Applications 4
5. Aims & Objectives
• Making a completely Embedded video/image
procuring system
• Developing a Wireless RF digital control
system for robot which is as user-friendly as
possible.
• Developing a surveillance system to observe
& monitor the surroundings as required by
user
5
6. Scope of Project
• Prototype model design of SPyDER is
capable of the following:
– Wireless RF digital control system
– 2-axis servo mount camera giving the robot wide range of
viewing even when it is stationary
– Wireless video transmission
– Speed control of DC motors through discrete PID controller
– Easy & Precise control for robot movement through joystick
– Autonomous obstacle detection & hurdle avoidance
6
12. Hardware Design
• The hardware section consist of two parts
– On-board SPyDER ; that is interfaced
with the Robot Assembly
&
– The other interfaced with the control
station; laptop & stand-alone joystick
module
12
13. Control Station
Control Module
COMMAND DATA ACQUISITION & TRANSMISSION
ANALOG HM-TR RF
AVR MICROCONTROLLER
JOYSTICK Transceiver
WARNING DISPLAY
13
15. On-board SPyDER
On-Board SPyDER Control
Circuitry
Proximity
Sensor/s
Hope HM-TR CAMERA PAN TILT
RF Transceiver ASSEMBLY
ANTENNA
Servo Motor
Servo Driver Elevation Control
Servo Motor
Servo Driver
MICROCONTROLLER
Azimuth Control
AVR ATmega16
ATmega16 ATmega16
H-BRIDGE H-BRIDGE
ENCODER ENCODER
WORM GEAR WORM GEAR
MOTOR MOTOR
RIGHT MOTOR DRIVE
LEFT MOTOR DRIVE
15
17. On-Board Robot Circuitry
• Implementation of Discrete PID
Controller on each DC Motor for
accurate speed control
• Two H-Bridges to control the direction
of DC motors for motion of SPyDER
• Two Servo motors for camera pan tilt
control
17
21. PID Controller
• A PID Controller attempts to correct the error b/w the
measured process variable & a desired set-point by
calculating & then outputting a corrective action that can
adjust the process accordingly
Discrete PID Controller
+
SPEED
MOTOR
PWM
Error CONTROLLER
Reference
-
ENCODER
REFERNECE: Charles L. Philips, Royce D. Harbor, Feedback Control Systems, Third Edition, (1996)
21
22. PID Controller Flow-chart
START
System Configuration
SPI Interrupt Get Reference
1
Error = Ref – Vel.Sensor Velocity Sensor
P-Out = Kp x Error
Integral error +=error
I-Out = Integral error x Ki
Derivative error = error - Prv error
D-Out = Derivative error x Kd
F-Out = I-Out + P-Out + D-Out
Prv error = Error 1
22
23. DC Motor Transfer Function
Here KM is the steady-state gain of the system and TM is known as the time-constant of the system
and is defined as the time at which the system output reaches the 63.2 % of the steady-state value.
• Equation 1 : (1)
Equation 2 shows the transfer functions obtained for each step applied.
• Equation 2 : (2)
where the values of TM and KM substituted for G1 through G3 are in milliseconds and RPMs
respectively.
Equation 3 displays the model obtained with this approximation.
• Equation 3 : (3)
Once we've derived the nominal model of the motor (Equation 3), we proceed to tune the parameters
of the PID controller.
REFERNECE: Makea PI controller on an 8-bit micro By Crescencio Hernandez-Rosales, Ricardo
Femat-Flores, and Griselda Quiroz-Compean
23
29. Firmware Design
Firmware includes all of the software required
to run the control systems involved in SPyDER
– Microcontroller programming in C language
– Developing GUI in Visual Basic
– Interface between Control Station and Robot
Hardware
29
30. Flowchart Control Command
Acquisition / Transmission
START
System Configuration
Input from JOYSTICK
Serial Communication Config.
(255,128)
(94,18)
ADC Conversion
Get Input from ADC Register
(255,128)
(128,128)
Arithmetic operation on raw data
(0,128)
Attach Pre-words
(128,0)
Transfer Data Through USART Transmission from HM-TR Transceiver
YES
If Sensors
Display Warning
Flag valid
NO
RETURN TO WAIT
FOR COMMAND 30
31. Control Word Transmission
The following Words are generated by the Base-Station Micro-controller to be transmitted
to the Embedded Controller on-board SPyDER .
PRE WORD REF LEFT REF RIGHT
(f,r,b,l) (0-36) (0-36)
31
32. Control Word Reception
The Words generated by the Base-station controller are received by the Embedded
Micro-controller on-board SPyDER and then sent to the PID controller circuit in the
following manner.
REF PRE WORD
(0-36) (f,r,b)
32
33. Flowchart Control Command
Reception / Implementation
START
System Configuration
Serial Communication Config.
Get Input from USART 0 Reception at HM-TR Transceiver
(Connected to HM-TR Transceiver)
Decoding & Comparison
Transfer Data to respective slave
mControllers through SPI
YES
If Sensor Send Warning to USART 0
Flag valid
NO
RETURN TO START
33
34. Joystick Control
The robot operates by using a simple PS2 joystick
• Following are the operation modes of SPyDER
– The main operation mode is simply the forward
and reverse motion simulated by the movement of
the analog joystick with variable speed
– The second operation mode; by pressing the
button with the ‘□’ symbol; is for initiating the
braking mechanism of SPyDER
– The third operation mode; by pressing the button
with the ‘∆’ symbol along with the analog joystick;
is for allowing SPyDER to accomplish compass
rotation
– The fourth operation mode; by pressing the button
with the ‘O’ symbol along with the analog joystick;
is for allowing SPyDER to accomplish axis
rotation
– The fifth operation mode; by pressing the button
with the ‘X’ symbol along with the analog joystick;
is also forward and reverse motion only the speed
in fixed at a particular value
34
35. Wireless (CCTV) Video Transmission
CCTV is the abbreviated form of closed circuit television that consists of a
television and some tiny cameras to record and play live events happening
within its cover area.
• Digital Video Recording (DVR) Cards:
These cards are purpose built for surveillance
systems. These cards have many advanced
function available and they are costlier as
compared to TV Tuner Cards. A digital video
recorder (DVR) or personal video recorder
(PVR) is a device that records video in a digital
format to a disk drive or other memory medium
within a device.
35
36. GUI
• A graphical user interface (GUI) is a graphical display
that contains devices, or components, that enable a user
to perform interactive tasks. To perform these tasks, the
user of the GUI does not have to create a script or type
commands at the command line. Often, the user does
not have to know the details of the task at hand.
• The GUI components can be menus, toolbars, push
buttons, radio buttons, list boxes, and sliders; just to
name a few.
• We have developed the GUI for video acquisition in
VISUAL BASIC.
36
38. System Limitations
• Constrained space available for Embedded
Electronics & batteries
• Speed resolution is restricted i.e. 0-33 steps due
to low resolution of speed sensor
• Electronic braking is not very effective at high
speeds
• Range for hurdle detection is 5cm
• The battery power consumption for controller &
motor driving circuitry is high
38
39. Practical Applications
– For traversing through complex terrains &
obstacles
– Surveillance of unreachable passageways &
unstructured environments
– Disaster area inspection
– Initial surveillance of potentially dangerous areas
– Mine field detection
– Earthquake Hazards
– Overt security surveillance
– For Military Monitoring purposes
39
40. References
• PID Control Theory Matt Krass http://www.team358.org/
by
• Maurice, B. quot;ST62 microcontrollers drive home appliance motor
technology, AN885/1196,quot; Application Note, ST Microelectronics,
1998, http://www.st.com/.
• Katausky, J., I. Horder, and L. Smith. quot;Analog/Digital Processing with
Microcontrollers,quot; AR-526 Applications Engineers, Intel
Corporation, http://www.intel.com/.
• Data sheet. quot;W78E858 8-bit microcontroller,quot; Winbond Electronics,
Rev. A4, May 2004.
• Data sheet. quot;DS5000T Soft microcontroller Module,quot; Dallas
Semiconductors,http://www.maxim-ic.com/.
• Make a PID controller on an 8-bit micro by Crescencio Hernandez-
Rosales, Ricardo Femat-Flores, and Griselda Quiroz-Compean
http://www.embedded.com/
40