Title of Publication : A Custom single purpose fixed point Processor Based System for Map Generation Using Ultrasound Sensors
Publisher:
ICEDSP 09 (IEEE - International Conference on Electronic Design and Signal Processing)
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Construction of sine and cosine hologram of brain tumor imageeSAT Journals
Abstract Optical Scanning Holography is a technique in which an image is scanned by Time Dependent Fresnel Zone Plate and its intensity information is encoded into a two dimensional hologram. This technique not only records amplitude but also the phase of the object in case of various applications such as optical remote sensing, 3D encoding and decoding, 3D TV system. Optical scanning holography is an electronic process which is flexible, programmable and also has the capability of parallel processing. It has become a powerful technique over digital holography technique as it provides a very high processing speed, good quality color appearance, better sharpness and high resolution. An optical Fourier transform technique is used for its processing. Optical scanning holography is a real time system which involves the principle of optical heterodyne scanning. This paper proposes the construction of sine and cosine hologram of biomedical image such as brain tumor by using optical scanning setup. The holograms generated by this approach will be used for detection of tumor cells when these holograms are processed further in the reconstruction stage which will visualize more information of such a malignant cells. In the present work the construction stage of the hologram with optical set up has been accomplished and the simulation results of the hologram are observed by using MATLAB tool. Key Words: — Holography, Heterodyne scanning, Fourier transform, Fresnel Zone Plate, Optical setup
This paper presents new algorithms for Field of Vision (FOV) computation which improve on existing work at high resolutions. FOV refers to the set of locations that are visible from a specific position in a scene of a computer game.
We review existing algorithms for FOV computation, describe their limitations, and present new algorithms which aim to address these limitations. We first present an algorithm which makes use of spatial data structures in a way which is new for FOV calculation. We then present a novel technique which updates a previously calculated FOV, rather than re-calculating an FOV from scratch.
We compare our algorithms to existing FOV algorithms and show they provide substantial improvements to running time. Our algorithms provide the largest improvement over existing FOV algorithms at highresolutions, thus allowing the possibility of the creation of high resolution FOV-based video games.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Construction of sine and cosine hologram of brain tumor imageeSAT Journals
Abstract Optical Scanning Holography is a technique in which an image is scanned by Time Dependent Fresnel Zone Plate and its intensity information is encoded into a two dimensional hologram. This technique not only records amplitude but also the phase of the object in case of various applications such as optical remote sensing, 3D encoding and decoding, 3D TV system. Optical scanning holography is an electronic process which is flexible, programmable and also has the capability of parallel processing. It has become a powerful technique over digital holography technique as it provides a very high processing speed, good quality color appearance, better sharpness and high resolution. An optical Fourier transform technique is used for its processing. Optical scanning holography is a real time system which involves the principle of optical heterodyne scanning. This paper proposes the construction of sine and cosine hologram of biomedical image such as brain tumor by using optical scanning setup. The holograms generated by this approach will be used for detection of tumor cells when these holograms are processed further in the reconstruction stage which will visualize more information of such a malignant cells. In the present work the construction stage of the hologram with optical set up has been accomplished and the simulation results of the hologram are observed by using MATLAB tool. Key Words: — Holography, Heterodyne scanning, Fourier transform, Fresnel Zone Plate, Optical setup
This paper presents new algorithms for Field of Vision (FOV) computation which improve on existing work at high resolutions. FOV refers to the set of locations that are visible from a specific position in a scene of a computer game.
We review existing algorithms for FOV computation, describe their limitations, and present new algorithms which aim to address these limitations. We first present an algorithm which makes use of spatial data structures in a way which is new for FOV calculation. We then present a novel technique which updates a previously calculated FOV, rather than re-calculating an FOV from scratch.
We compare our algorithms to existing FOV algorithms and show they provide substantial improvements to running time. Our algorithms provide the largest improvement over existing FOV algorithms at highresolutions, thus allowing the possibility of the creation of high resolution FOV-based video games.
Range Free Localization using Expected Hop Progress in Wireless Sensor NetworkAM Publications
Wireless sensor network (WSN) combines the concept of wireless network with sensors. Wireless Sensor Networks
have been proposed for a multitude of location-dependent applications. Localization (location estimation) capability is
essential in most wireless sensor network applications. In environmental monitoring applications such as animal habitat
monitoring, bush fire surveillance, water quality monitoring and precision agriculture, the measurement data are
meaningless without an accurate knowledge of the location from where the data are obtained. Finding position without the
aid of GPS in each node of an ad hoc network is important in cases where GPS is either not accessible, or not practical to use
due to power, form factor or line of sight conditions. So here we are going to used DV-Hop algorithm, i.e. distance vector
routing algorithm for finding the position of sensor. Here we summarizes the performance evaluation criteria of the
wireless sensor network and algorithms, classification methods, and highlights the principles and characteristics of the
algorithm and system representative of the field in recent years, and several algorithms simulation and analysis.
A new approach for an intelligent swarm robotic systemeSAT Journals
Abstract Swarm robotics generally faces problems such as regular human interference, monitoring and lack of precision in accomplishing a task . These problems can be avoided by endorsing a new multi robot system .The tasks which are highly demanding and generally which cannot be accomplished by a single robot can be accomplished through Swarm Robotics which involves a group of robots. The multi robot system comprises of a drone(quadcopter) controlling and commanding the ground robots in order to accomplish the task. This approach preserves the versatility of each individual in the swarm and also establishes coordinative and cognitive behavior. The drone activates the ground robots and also monitors the movement of each ground robot. The ground robots also interact with each other to complete a task .This approach ensures complete autonomy and precision. Key Words: multi robot, drone, autonomy, versatility, Swarm robotics.
Design and Implementation of Area Optimized, Low Complexity CMOS 32nm Technol...IJERA Editor
A numerically controlled oscillator (NCO) is a digital signal generator which is a very important block in many Digital Communication Systems such as Software Defined Radios, Digital Radio set and Modems, Down/Up converters for Cellular and PCS base stations etc. NCO creates a synchronous, discrete-time, discrete-valued representation of a sinusoidal waveform. This paper implements the development and design of CMOS look up Table based numerically controlled oscillator which improves the performance, reduces the power & area requirement. The design is implemented with CMOS 32 nm Technology with Microwind 3.8 software tool. In addition, it can be used for analog circuit also enables the integration of complete system on chip. This paper also describes the design of a NCO which is of contemporary nature with reasonable speed, resolution and linearity with lower power, low area. For all about Pre Layout simulation has been realized using 32nm CMOS process Technology.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
This document describes the data processing flow in oblu. It also describes communication protocol using which one can access & control the data, set internal parameters and the processing at various stages, through an external
application platform.
---
Oblu is an opensource development board for wearable motion sensing. It is also an Arduino compatible programmable IMU for diverse inertial sensing applications. It comes pre-programmed as a shoe-mounted pedestrian dead reckoning PDR sensor for indoor navigation and personnel tracking. Real time tracking of first responders, robot navigation, geo-survey, understanding physics of motion, activity monitoring of elderly, gaming, VR etc are only few from the long list of applications which have been demonstrated using oblu.
Oblu is battery operable and uses Bluetooth Low Energy BLE for wireless data transmission. It is easily configurable and comes along with an Android application Xoblu for personnel tracking, a PC-based tool MIMUscope for detailed analysis and hardware accessories for ease of usage. It is based on opensource OpenShoe platform. Since beginning, Oblu has been distributed in 22 countries, to students, DIY enthusiasts, industrial & academic researchers, entrepreneurs etc. Oblu comes from the makers of Inertial Elements which is a famous for making multi-IMU array modules available commercially.
An Experimental Study on a Pedestrian Tracking Deviceoblu.io
The implemented navigational algorithm of an inertial
navigation system (INS), along with the hardware configuration, decides its tracking performance. Besides, operating conditions also influence its tracking performance. The aim of this study is to demonstrate robust performance of a multiple Inertial Measurement Units (IMUs) based foot-mounted INS, The Osmium MIMU22BTP, under varying operating conditions. The device, which performs zero-velocity-update (ZUPT) aided navigation, is subjected to different conditions which could potentially influence gait of its wearer, its hardware configuration etc. The gait-influencing factors chosen for study are shoe type, walking surface, path profile and walking speed. Besides, the tracking performance of the device is also studied for different number of on-board IMUs and the ambient temperature. The tracking performance of MIMU22BTP is reported for all these factors and benchmarked using identified performance metrics. We observe very robust tracking performance of MIMU22BTP. The average relative errors are less than 3 to 4% under all the conditions, with respect to drift, distance and height, indicating a potential for a variety of location based services based on foot mounted inertial sensing and dead reckoning.
Due to new developed technology man is leading a comfortable life. People want each work should be done automatically. So in this paper introduces a system called UNMANNED GROUND VEHICLE. UGV as name indicate it operates in contact with ground and without any human resource. The vehicle will have a set of sensors to observe the environment. In this paper for the working of UGV, FPGA is embedded with image processing. FPGA as main processing platform used to control UGV. The performance evaluation of proposed system takes place by capturing the image of UGV with help of camera. This system demonstrate accurate localization of UGV. This UGV vehicle used in military, mall, automobile industry. To work system properly provide proper interfacing and synchronization between hardware/software module.
Location Fingerprinting is a very familiar Wi-Fi positioning method, which determines a device by retrieving the information recorded containing the location fingerprint. These methods deploy the signal strength (RSS) to predict the coordinate. There are feedbacks for using the absolute RSS either the absolute RSS in a time interval may not be representable of the IEEE 802.11 signal, as the signal may fluctuate or a manual error prone calibration is needed across different mobile platform. The main target is to propose the use of Fourier descriptors in LF. We convert the IEEE 802.11b Wi-Fi signal into a Fourier domain. Then, the Fourier descriptors are used to predict the location by applying the K-Nearest Neighbor algorithm. The results show that the effectiveness of LF methods based on Fourier descriptors lead to substantially more accurate and robust localization.
Range Free Localization using Expected Hop Progress in Wireless Sensor NetworkAM Publications
Wireless sensor network (WSN) combines the concept of wireless network with sensors. Wireless Sensor Networks
have been proposed for a multitude of location-dependent applications. Localization (location estimation) capability is
essential in most wireless sensor network applications. In environmental monitoring applications such as animal habitat
monitoring, bush fire surveillance, water quality monitoring and precision agriculture, the measurement data are
meaningless without an accurate knowledge of the location from where the data are obtained. Finding position without the
aid of GPS in each node of an ad hoc network is important in cases where GPS is either not accessible, or not practical to use
due to power, form factor or line of sight conditions. So here we are going to used DV-Hop algorithm, i.e. distance vector
routing algorithm for finding the position of sensor. Here we summarizes the performance evaluation criteria of the
wireless sensor network and algorithms, classification methods, and highlights the principles and characteristics of the
algorithm and system representative of the field in recent years, and several algorithms simulation and analysis.
A new approach for an intelligent swarm robotic systemeSAT Journals
Abstract Swarm robotics generally faces problems such as regular human interference, monitoring and lack of precision in accomplishing a task . These problems can be avoided by endorsing a new multi robot system .The tasks which are highly demanding and generally which cannot be accomplished by a single robot can be accomplished through Swarm Robotics which involves a group of robots. The multi robot system comprises of a drone(quadcopter) controlling and commanding the ground robots in order to accomplish the task. This approach preserves the versatility of each individual in the swarm and also establishes coordinative and cognitive behavior. The drone activates the ground robots and also monitors the movement of each ground robot. The ground robots also interact with each other to complete a task .This approach ensures complete autonomy and precision. Key Words: multi robot, drone, autonomy, versatility, Swarm robotics.
Design and Implementation of Area Optimized, Low Complexity CMOS 32nm Technol...IJERA Editor
A numerically controlled oscillator (NCO) is a digital signal generator which is a very important block in many Digital Communication Systems such as Software Defined Radios, Digital Radio set and Modems, Down/Up converters for Cellular and PCS base stations etc. NCO creates a synchronous, discrete-time, discrete-valued representation of a sinusoidal waveform. This paper implements the development and design of CMOS look up Table based numerically controlled oscillator which improves the performance, reduces the power & area requirement. The design is implemented with CMOS 32 nm Technology with Microwind 3.8 software tool. In addition, it can be used for analog circuit also enables the integration of complete system on chip. This paper also describes the design of a NCO which is of contemporary nature with reasonable speed, resolution and linearity with lower power, low area. For all about Pre Layout simulation has been realized using 32nm CMOS process Technology.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
This document describes the data processing flow in oblu. It also describes communication protocol using which one can access & control the data, set internal parameters and the processing at various stages, through an external
application platform.
---
Oblu is an opensource development board for wearable motion sensing. It is also an Arduino compatible programmable IMU for diverse inertial sensing applications. It comes pre-programmed as a shoe-mounted pedestrian dead reckoning PDR sensor for indoor navigation and personnel tracking. Real time tracking of first responders, robot navigation, geo-survey, understanding physics of motion, activity monitoring of elderly, gaming, VR etc are only few from the long list of applications which have been demonstrated using oblu.
Oblu is battery operable and uses Bluetooth Low Energy BLE for wireless data transmission. It is easily configurable and comes along with an Android application Xoblu for personnel tracking, a PC-based tool MIMUscope for detailed analysis and hardware accessories for ease of usage. It is based on opensource OpenShoe platform. Since beginning, Oblu has been distributed in 22 countries, to students, DIY enthusiasts, industrial & academic researchers, entrepreneurs etc. Oblu comes from the makers of Inertial Elements which is a famous for making multi-IMU array modules available commercially.
An Experimental Study on a Pedestrian Tracking Deviceoblu.io
The implemented navigational algorithm of an inertial
navigation system (INS), along with the hardware configuration, decides its tracking performance. Besides, operating conditions also influence its tracking performance. The aim of this study is to demonstrate robust performance of a multiple Inertial Measurement Units (IMUs) based foot-mounted INS, The Osmium MIMU22BTP, under varying operating conditions. The device, which performs zero-velocity-update (ZUPT) aided navigation, is subjected to different conditions which could potentially influence gait of its wearer, its hardware configuration etc. The gait-influencing factors chosen for study are shoe type, walking surface, path profile and walking speed. Besides, the tracking performance of the device is also studied for different number of on-board IMUs and the ambient temperature. The tracking performance of MIMU22BTP is reported for all these factors and benchmarked using identified performance metrics. We observe very robust tracking performance of MIMU22BTP. The average relative errors are less than 3 to 4% under all the conditions, with respect to drift, distance and height, indicating a potential for a variety of location based services based on foot mounted inertial sensing and dead reckoning.
Due to new developed technology man is leading a comfortable life. People want each work should be done automatically. So in this paper introduces a system called UNMANNED GROUND VEHICLE. UGV as name indicate it operates in contact with ground and without any human resource. The vehicle will have a set of sensors to observe the environment. In this paper for the working of UGV, FPGA is embedded with image processing. FPGA as main processing platform used to control UGV. The performance evaluation of proposed system takes place by capturing the image of UGV with help of camera. This system demonstrate accurate localization of UGV. This UGV vehicle used in military, mall, automobile industry. To work system properly provide proper interfacing and synchronization between hardware/software module.
Location Fingerprinting is a very familiar Wi-Fi positioning method, which determines a device by retrieving the information recorded containing the location fingerprint. These methods deploy the signal strength (RSS) to predict the coordinate. There are feedbacks for using the absolute RSS either the absolute RSS in a time interval may not be representable of the IEEE 802.11 signal, as the signal may fluctuate or a manual error prone calibration is needed across different mobile platform. The main target is to propose the use of Fourier descriptors in LF. We convert the IEEE 802.11b Wi-Fi signal into a Fourier domain. Then, the Fourier descriptors are used to predict the location by applying the K-Nearest Neighbor algorithm. The results show that the effectiveness of LF methods based on Fourier descriptors lead to substantially more accurate and robust localization.
The autonomous Test Bench is the growing field of
testing device. The Rapid production firms require rapid testing
infrastructure. Many firms till now use legacy system. The
Autonomous Test Bench is a Rapid Application Development tool
to accelerate the device testing rapid. To implementation ATB
(Autonomous Test Bench) the major requirement is to measure
the target object distance from robotic arm to trigger the device
(like push button, gripping something etc.) Not only Robotic
system, many fields of industry are required to capture ultrasonic
scan data. Sometimes it should be wireless system which may be
positioned anywhere. This paper describes a novel way to capture
surrounded ultrasonic scan data. The device is portable and
wireless and as well as cost effective. To measure object distance,
ultrasonic peripatetic scanner uses two servo motors to scan the
object horizontally and vertically. The main controller is a credit
card sized computer Raspberry pi with high processing capability
and portability. The programs are written using Python which is
an interpreted language.
Spatial Correlation Based Medium Access Control Protocol Using DSR & AODV Rou...IOSR Journals
Abstract : In Wireless sensor network sensor nodes have a limited battery life and their efficient utilization is
a very much importent task. Their are many ways are proposed for efficient utilization of energy.For efficient
energy utilization many topologies,protocals are proposed by the help of which we can maximize the battery
life. In this paper we propesed a methode in which a correlation is made between all the sensor nodes including
ME(mobile element). A Vector Quantization methode are used for distance calculation between all the sensor
nodes and mobile element. After finding the corrélation we used the DSR & AODV routing Protocol. The
performance of the proposed protocol has been examined and evaluated with the NS-2 simulator in terms of
packet drop ratio and energy consumption. The simulation result shows that the proposed protocol with AODV
routing gives a batter result compared with same protocol with DSR routing.
Keywords: ME, DVT, DSR, AODV, Wireless Sensor Network, Efficient Energy Utilization
Ant Colony Optimization for Wireless Sensor Network: A Reviewiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Complete report on DATA ACQUISITION SCHEME IN WIRELESS SENSOR NETWORKRutvik Pensionwar
With the development in data acquisition system, information-collection plays an increasingly important role in the field of Wireless Technology. There has been tremendous increase in the use of sensors in each and every field. In order to get fast response from these sensors the delay should be reduced. Also the congestion in the network should be tackled to increase the efficiency. Wireless Sensor Networks (WSNs) consist of many tiny wireless sensors which operate in an environment in order to collect data. In a typical WSN, data is gathered from environment by sensor nodes and then transmitted to a base station. All these operations are executed by sensor nodes with keeping in mind the limitation of power. Reliable communication, power efficiency, network congestion issues are among major concerns. So in our project our main focus is to avoid the packet loss by increasing the network efficiency and handling the congestion in the network by proper buffer management. Finally visualization of processed data is done at the base station and the future enhancement could be to directly send the sensed data to cloud storage.
Adaptive Monitoring and Localization of Faulty Node in a Wireless Sensor Netw...Onyebuchi nosiri
Abstract
This work seeks to solve the problem that is being experienced in most existing remote monitoring systems by coming up with an enhanced monitoring system called Wireless Sensor Network. A Personal Area Network was evolved to increase the coverage area by spatially distributing Sensor nodes to capture and transmit physical parameters like temperature and Carbon monoxide in an indoor local cooking environment. Faulty node detection and localization was also realized, this was achieved by coming up with an algorithm that logically considers the receive signal strength value of -100 dbm as threshold, Result of data transmitted were viewed via a C-Sharp interface for Adaptive monitoring. The result from the Visual Basic plot shows that the Sensor nodes were able to capture temperature range of between 250C to 510C while the result of the CO emission shows an interval of 0.01g/m3 to 30.0 g/m3. A comparison between data transmitted at source and data received at the destination (sink) was carried out, a ranking test was used to validate the data received, a 0.9325 correlation value was obtained which shows a high level of integrity of 93.25% .
Recent advances in radio and embedded systems for completing the procedure of location estimation most
of the time sensor networks are fully dependent on the distance measurements that is present between the
sensor neighbourhood node. Techniques used for the localization can be categorized differently.
Techniques used for the measurement of the distance between the wireless sensor nodes, dependent upon
the physical means are divided into three broader categories namely Received signal strength (RSS), Angle
of Arrival (AOA) and propagation base on time measurements. This paper discusses the most of the
approached of WSN and IoT based positioning system.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Investigations on real time RSSI based outdoor target tracking using kalman f...IJECEIAES
Target tracking is essential for localization and many other applications in Wireless Sensor Networks (WSNs). Kalman filter is used to reduce measurement noise in target tracking. In this research TelosB motes are used to measure Received Signal Strength Indication (RSSI). RSSI measurement doesn‟t require any external hardware compare to other distance estimation methods such as Time of Arrival (TOA), Time Difference of Arrival (TDoA) and Angle of Arrival (AoA). Distances between beacon and non-anchor nodes are estimated using the measured RSSI values. Position of the nonanchor node is estimated after finding the distance between beacon and nonanchor nodes. A new algorithm is proposed with Kalman filter for location estimation and target tracking in order to improve localization accuracy called as MoteTrack InOut system. This system is implemented in real time for indoor and outdoor tracking. Localization error reduction obtained in an outdoor environment is 75%.
Technoblade The Legacy of a Minecraft Legend.Techno Merch
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Can AI do good? at 'offtheCanvas' India HCI preludeAlan Dix
Invited talk at 'offtheCanvas' IndiaHCI prelude, 29th June 2024.
https://www.alandix.com/academic/talks/offtheCanvas-IndiaHCI2024/
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1. IC09-171/118
A Custom single purpose fixed point Processor Based
System for Map Generation Using Ultrasound
Sensors
Prabhakar Mishra†, H N Shankar††, Avinash Gokhale*, Rakshith Shetty*, Kiran Kumar Mangond*, Shashank V*
†
Author for correspondence, Department of Telecommunication Engineering, PESIT, Bangalore
††
Department of Telecommunication Engineering,*Department of Electronics and Communication Engineering, PESIT,
Bangalore
1
prabhakar.mishra@pes.edu
hnshankar@pes.edu
Abstract— In this paper, in motion mapping of the real world as
perceived by a robot using a real time embedded system based on
a custom single purpose fixed point processor is proposed. The
processor is optimized for low power and is used for acquiring
the range reading from a set of ultrasound sensors and calculating
the probability of occupancy of cells in the region under the sonar
scan . The architecture considerably lowers the switching activity
at various stages of acquiring and processing the sensor data to
provide updates of cell occupancy values for rapid in-motion
mapping for robot navigation. Various mapping strategies using
the system are evaluated for their efficacy and computational
complexity.
Keywords—Autonomous robot navigation, Low-power design,
Occupancy grids, Ultrasound sensors.
I. INTRODUCTION
Autonomous robot navigation in unknown and unstructured Fig. 1 The Sonar Model
environments is central to many industrial and research
applications. It involves creation of a world model of the R is the range measurement returned by the sonar sensor
environment of the robot using sensory data and orientation of ε is the mean sonar deviation error
the robot. Previous works in this area include the use of ultra- ω is the beam aperture
sound sensors for map generation using occupancy grids. [1] S (x, y, z) is the position of the sonar sensor
Many mapping techniques use a probabilistic approach to δ is the distance between P and S
detect the presence or absence of obstacles in the environment θ is the distance between the main axis and SP
as perceived by the robot. The sonar sensor’s data range is
divided into cells and probability functions are applied on them In the method proposed by [2], the mapping is based on
to ascertain if the cell is empty or occupied. The map is evaluation of probability of cells being occupied or empty.
incrementally updated based on Bayesian estimation In the empty region, the probability is calculated using the
procedures to improve the map definition. formula
The sensor array consists of 24 transducers arranged as a
ring, each spaced 15º apart to cover the entire 360º panorama PE(X, Y) = Er (δ) * Ea (θ)
around the robot. Each sensor has a beam width of 30º and a
maximum range of 20 feet. The sensors in close vicinity are
fired sequentially to avoid interference and each sensor reading
is converted into a probability profile.
The sonar beam is divided into two parts, empty region and
somewhere occupied region [1],[2]. The final sonar map is a Er (δ) is the estimation that the cell is empty based on its
two-dimensional array of cells with values ranging between (0, range from the sensor. The closer it is to the sensor, the more
1). The values below a certain threshold are considered likely that it is not occupied.
probably empty and the values above it are considered
probably occupied. Fig. 1 shows the sonar model and
associated parameters.
2. IC09-171/118
Ea(θ) is the estimation that a cell is unoccupied based on the Freelancer is powered by two sources – one for drive and one
difference in angle between it and the central beam of the for control. It can take a payload of 5.8 Kg with a top speed of
sonar, θ. Cells closer to the central beam of the sonar are more 30cm/s.
strongly updated as empty than cells near the extremities of the
beam.
The probability that the cell is occupied is calculated using
the formula,
PO(X, Y) = Or (δ) * Oa (θ)
Or = 0 otherwise.
Or (δ) is the probability that the cell is occupied based on its
range from the sensor. The closer it is to the range reading
received, the higher the probability that the cell is occupied.
Oa (θ) is the probability that the cell is occupied based on the Fig. 3 Schematic of the control architecture for freelancer
difference in angle between the obstacle and the central beam
of the sonar. The closer the cell is to the centre of the beam, the The overall schematic of the control architecture is shown in
more likely it is that the cell is occupied. fig 3. The Intermediate Processing Unit (IPU) takes the sensor
These probability values are calculated and thresholding is inputs and generates different descriptions of the world model;
applied wherein the values below a certain upper bound and these are the inputs to different algorithms as per their
above a certain lower bound are treated as the end points of the individual requirements. In addition, the IPU generates an
range of probability values. estimate of the obstacle density in the polar reference frame.
This in turn is used to decide whether or not a path with
Our robot- freelancer sufficient clearance exists within a specific range and in a
specific orientation in relation to the current state of the robot.
The inputs to the fuzzy controller are the speed commands and
the steering commands of the individual algorithms along with
the polar obstacle density. The fuzzy controller outputs the
speed and angle control. This is transformed into PWM signals
for the individual drive motors. The details of these are omitted
here.
II. THE EMBEDDED DATA ACQUISITION SYSTEM
Sensor data acquisition and evaluation of the probability
values imposes significant overheads on the processor time.
Hence a single purpose fixed-point processor supporting multi-
channel ultrasound sensor interface and dedicated memory
Fig. 2 Our robot freelancer.
block is used in the present system.
Freelancer as shown in Fig 2, is our multi-sensor robot. It In this method, the processing sequence of one sonar scan
measures 65cm×45cm×40cm with ground clearance 8cm. It includes the following steps.
has a four-wheel differential drive. It has (i) provision for up to The sonar sensor returns a pulse whose width is
24 sonar sensors, Devantech SRF-04/07/08, currently it has proportional to the range of the obstacle.
one at each corner for detection and ranging of obstacles up to This pulse is used to enable an 8-bit counter.
3m; (ii) 15 infrared LED sensor pairs to detect obstacles in The range value and the constants used in the evaluation
close proximity of the robot to facilitate guiding through a of the probability are stored in a set of registers.
clutter of closely spaced obstacles; and (iii) a Devantech A fixed-point ALU with separate instances of adder and
CMPS03 digital compass for precise orientation. The Logitech multiplier calculate the probabilities and a finite state
webcam seen in the front has been mounted very recently. machine sequences the flow of operands.
Freelancer has a distributed control architecture with an Two RAM areas hold the values of probability of empty
IRFZ44N MOSFET based full-bridge chopper drive in Class E and occupied cells which is used by the main processor
configuration and driven by ATMEGA 88 microcontroller. The for generating and updating the map of the environment
top level processing unit is built around an AMD Athlon 2600+ as perceived by the robot.
processor and an ASUS A7S266-VM/U2 mother board.
3. IC09-171/118
The architecture of the custom fixed point processor based the sensor when looking at the cell. Each cell has a N-size
system is shown in Fig. 4. array associated which stores cell responses in N-directions, as
resp[i] (index i corresponds to ith direction wrt a fixed
reference).
The original response grid method has the following
probability function
α
,δ = R
P(occupied) = δ
0.05, δ <
0.5, δ >
where α is normalising constant.
The resp[i]’s are updated using the Bayesian formula as
resp[i] ∗ P(occupied)
resp[i] =
resp[i] ∗ P(occupied) + (1 − resp[i]) ∗ (1 − P(occupied)
The N-responses are combined to give final occupancy as
Occupancy = 1 − (1 − resp[i])
Modified method:
Fig. 4 Custom single purpose fixed-point processor architecture for data The main modification is that we have changed the function
acquisition and calculation of probability of empty and occupied cells. P(occupied) to
. Rmax − δ (halfangle − θ)
P(occupied) = + when R − ε < δ < −ε
Rmax halfangle
III. OUR PROPOSED SOLUTION where k is a constant. The value of k gives the weightage to
the readings in proximity.
P(occupied) = 0.5 when δ > R + ε
And here we don’t store responses from all the n directions
but instead store only the maximum response considering all
directions and the direction in which maximum response was
obtained. So each cell has a 1 X 2 array associated with it
where the 1st value (max_resp[0]) is the maximum response it
generated and the 2nd (max_resp[1]) is the direction. They are
initialized to 0 and -1 respectively.
Now if a cell falls in the somewhere occupied region of the
sonar beam and its response, given by P(occupied) is greater
than the stored maximum (max_resp[0]) then this value and the
Fig. 5 Test area. corresponding direction is stored in the max_resp array.
The test area shown in Fig. 5 consists of a long narrow If a cell falls in the empty region of the sonar beam then its
corridor with adjacent walls being taller than the sensor value is updated only if the current reading’s direction is same
mounting. The region is highly specular and the mapping as that of the stored maximum. By this we reduce the effect of
methods described in [1],[2],[6], did not generate satisfactory false readings while preserving advantage of response grid
map. method. The final occupancy is the stored maximum value.
The method proposed here is the modification of response IV. RESULTS AND CONCLUSION
grid method described in [9]. In response grid method the Both methods were tested on the environment described
occupancy value assigned to each cell depends not only on the previously and the resulting maps generated are shown
distance of the cell from the sensor, but also the orientation of
4. IC09-171/118
Fig. 6 shows the map generated using original response grid
method for N=16. It is evident from the map that the walls are
not distinct and feature extraction is difficult and cannot be
done using simple thresholding.
Fig. 7 shows the map that is generated using modified
response grid method. It might look clumsy but by applying
simple threshold, obstacles can be extracted. Fig. 8 and Fig. 9
illustrate this.
Fig. 8 is the map obtained for modified response grid for
k=2 and thresholding of 0.90. Here the walls are distinct and
can be used for feature extraction.
Fig. 9 the map obtained for modified response grid for k=4
and thresholding of 0.90. Again the walls are distinct. Fig. 8
In the modified method, memory usage and computations
are independent of N. But the original method requires N+1
fixed point values per cell and N multiplications per update.
The results are tabulated below.
Original response Modified response
grid Method grid method
N=16 N=16
Time taken▲ (in ms) 473 460
Memory used (per 17 fixed point 2 fixed point values
cell) values
▲: involved 103,520 map updates.
Fig. 9
ACKNOWLEDGMENT
We thank the management of PESIT for providing us with
the support needed for the work.
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Fig. 7