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[Gp][1st seminar][presentation]
1. Computer and Information Science | Computer Systems Department
1st Seminar 28/2/2013
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 11st Seminar
2. • Team
– Ahmed Mohamed Emad
– Abdelrahman Ehab Soliman
– Muhammed Aly Huessin
– Anas Awad Ismail
• Academic Supervisors
– Prof. Hossam El-Din Fahem
– Dr. Wael S. El-Kilany
– TA. Agwad Hammad
Team Members
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 21st Seminar
3. • Area Exploration Problem:
– Problem definition.
– Previous Work.
• Cooperative Swarm:
– Swarm Robotics
– Why Swarm?!
– Goal.
– Frontier-Based Exploration.
– System Architecture.
• Robots Capabilities:
– Sensors, Brains, Cameras, … etc.
– Tools and Environment.
• Timeline:
– Our Status.
Outline Introduction Co-Swarm Timeline References
Outline
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 31st Seminar
4. Problem Definition
“In Robotics, the exploration problem deals with the use
of a robot to maximize the knowledge over a
particular area. The exploration problem arises in
mapping and search and rescue situations, where an
environment might be dangerous or inaccessible to
humans ”
Outline Introduction Co-Swarm Timeline References
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 41st Seminar
Introduction|Area Exploration
5. Problem Overview
– The exploration problems appeared when the humans think to use
robots to discover unknown areas that may be dangerous or
inaccessible for humans.
– Robot needs a map to operate in a particular environment.
– Autonomous Exploration : The ability of robots to autonomously
travel around an unknown environment gathering the necessary
information to obtain a useful map for navigation.
– Optimization Problem
Outline Introduction Co-Swarm Timeline References
Introduction|Area Exploration
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 51st Seminar
6. Previous Work
• In absence of global position information, (SLAM) techniques are
deployed to construct a map.
• State of the art:
– Classic non-coordinated strategies
– Classic coordinated strategies
– Integrated non-coordinated strategies
– Integrated coordinated strategies
Outline Introduction Co-Swarm Timeline Our Status
Introduction|Area Exploration
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 61st Seminar
7. Previous Work
• In absence of global position information, (SLAM) techniques are
deployed to construct a map.
• State of the art:
– Classic non-coordinated strategies
– Classic coordinated strategies
• Frontier-Based Exploration using Multiple Robots – Brain Yamuchi 1998
– Integrated non-coordinated strategies
– Integrated coordinated strategies
Outline Introduction Co-Swarm Timeline Our Status
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 71st Seminar
Introduction|Area Exploration
8. What’s Swarm ?!!
• New bio-inspired approach to control the coordination of (Multi-Robot
System)MRS, which consists of large numbers of mostly simple
physical robots.
• This collective behavior leads to the field of Artificial Swarm
Intelligence.
Outline Introduction Co-Swarm Timeline References
Co-Swarm | Swarm Robotics
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 81st Seminar
9. Why Swarm ?!!
• Simple and Elegant.
– Can be represented by State Machine.
• Scalable.
• Decentralized.
• Usage of local interactions.
Outline Introduction Co-Swarm Timeline References
Co-Swarm | Swarm Robotics
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 91st Seminar
10.
11. Central Idea
• Gain the most new information about the world.
• Move to the boundary between open space and uncharted space.
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Frontier-Based Exploration
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 111st Seminar
12. Evidence Grid
• Our Spatial Representation for the Environment.
• A Cartesian Grid containing cells and each cell contains its state
whether it is Open , Occupied or unknown.
Frontier Detection
• Frontiers are regions on the boundary between open space and
unexplored space.
• A process analogous to edge detection and region extraction in
computer vision is used to find the boundaries between open
space and unknown space.
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Frontier-Based Exploration
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 121st Seminar
13. Navigate to Frontiers
• The robot attempts to navigate to the nearest accessible
unvisited frontier.
• Motion Planning with Obstacle Avoidance.
• Path Finding Algorithm A*.
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Frontier-Based Exploration
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 131st Seminar
14. Outline Introduction Co-Swarm Timeline References
Co-Swarm |Frontier-Based Exploration
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 141st Seminar
15. Multi-Robot Exploration
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Frontier-Based Exploration
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 151st Seminar
16. Outline Introduction Co-Swarm Timeline References
Co-Swarm |System Architecture
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 161st Seminar
17. Outline Introduction Co-Swarm Timeline References
Co-Swarm |System Architecture
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 171st Seminar
18. Robocars
• 4-wheels car:
– with 4 DC motors and encoders
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Capabilities
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 181st Seminar
19. Microcontroller
• ISP flash memory for 128 KB Internal Programming.
• 4 KB EEPROM.
• 4 KB Internal SRAM.
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Capabilities
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 191st Seminar
20. Sensors
• Position Sensitive Device (PSD)
– Range: 10 cm 80 cm
• Ultrasonic :
– Range: 10 cm 10 m
• Infra-red:
– For line tracking Applications
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Capabilities
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 201st Seminar
21. Bluetooth Module
• Used in communication to exchange map information
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Capabilities
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 211st Seminar
22. Camera
• Our system will not depend on vision system.
• Capturing the surroundings and pass the data to a base
station.
– 3D Area reconstruction.
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Capabilities
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 221st Seminar
23. Brains
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Capabilities
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 231st Seminar
24. Brains
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Capabilities
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 241st Seminar
25. • AVR Studio
Outline Introduction Co-Swarm Timeline References
Co-Swarm |Tools and Environment
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 251st Seminar
26. Outline Introduction Co-Swarm Timeline References
Timeline
ID Task name start finish 11 12 1 2 3 4 5
1 problem characterization 1/11 15/11
2 literature survey on cooperative
mapping using multirobot systems
15/11 1/1
3 Testing robo-car capabilities 15/11 15/12
4 Developing a set of simple
behaviors to control the motion of
robo-car, obstacle avoidance
25/1 20/2
5 Developing a robo-car framework
to work with
20/2 6/3
6 Implementing exploration on one
robot
25/2 10/3
7 Developing a fusion technique for
combining local maps into global
map
10/3 5/4
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 261st Seminar
27. Outline Introduction Co-Swarm Timeline References
Timeline
ID Task name Start finis
h
11 12 1 2 3 4 5
8 Studying coordinated mobility
model mobility and anti-flocking
model mobility and their effect on
the mapping process
10/3 5/4
9 Implementation 15/11 1/5
10 Performance evaluation and
refinement
15/4 15/5
11 Final Report 1/12 30/5
12 Presentation and final delivery
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 271st Seminar
28.
29.
30. Framework
• Robot Motion:
– Description
– PID Control
Outline Introduction Co-Swarm Timeline References
Timeline| Our Status
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 301st Seminar
31. Outline Introduction Co-Swarm Timeline References
Timeline| Our Status
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 311st Seminar
D=2*∏*r
r= 42 mm
∅=D/R
R= 116 mm
VL /(R-L/2) = VR /(R+L/2)
L = 24 cm
32. Outline Introduction Co-Swarm Timeline References
Timeline| Our Status
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 321st Seminar
Framework
– Control Theory
• Systems (Velocity) : it is the component which describe what is the system doing now .
• System output (Rotations): is the result or the signals which generating from the system .
• Sensor(Encoder): it is the feedback system which can sense the output of the system .
• Reference(Target Velocity) : it is the target of the system or what we need the system
actually do.
• Controller(PWM) : the component which convert the Measured error to control signals.
33. Framework
• Motion Control : PID Control
Outline Introduction Co-Swarm Timeline References
Timeline| Our Status
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 331st Seminar
34. Framework
• Motion Control :
– PID Control effect
Outline Introduction Co-Swarm Timeline References
Timeline| Our Status
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 341st Seminar
35. Framework
• PID Control:
Outline Introduction Co-Swarm Timeline References
Timeline| Our Status
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 351st Seminar
36. Framework
• Communication:
– Sending and receiving data using Bluetooth
Outline Introduction Co-Swarm Timeline References
Timeline| Our Status
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 361st Seminar
37.
38. Area Exploration
Outline Introduction Co-Swarm Timeline References
Timeline| Our Status
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 381st Seminar
Stop
Avoid
Obstacles
Rotate
Move
Gather Information &
Creating Local Grid
Explore
No Avail. Path
Avail. Path
Find obstacle
New path
New path
39. Area Exploration
• Now , We are working on the following :-
– Implementation of a mapping technique.
– Implementation path planning:
• Data Structure Metric Mapping.
• Algorithm A* for static environment .
Outline Introduction Co-Swarm Timeline References
Timeline| Our Status
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 391st Seminar
40. • Frontier-Based Exploration Using Multiple Robots – Brain
Yamauchi – 1998.
• A Frontier-Based Approach for Autonomous Exploration –
Brain Yamauchi – 1997.
• A comparison of path planning strategies for autonomous
exploration and mapping of unknown environments – Miguel
Juliá – 2012.
• Probabilistic Robotics – Sebastian Thrun.
• An Introduction to AI Robotics – Robin R. Murphy.
• Embedded Robotics – Thomas Braunl.
• Robocar user Manual.
Outline Introduction Co-Swarm Timeline References
References
Co-Swarm: Cooperative area exploration using a swarm of mobile robots February 2013 401st Seminar
Notas del editor
As the robots move to unexplored zones, these zones are included in the map.Thus, the problem of autonomous exploration could be understood as a traveling salesman problem where the robot must plan the order to visit the remaining unexplored zones while minimizing the total traveled distance.This way, there are greedy approaches where the robots move to the nearest or biggest unexplored zone, and more elaborated heuristic approaches. However, this is dynamic process in which the set of places to visit is changing continuously.
Classic non-coordinated strategiesUsing one Robot only in exploration to acquire as mush information as possible in a short time, they don’t care about localization Yamauchi 1997 (Frontier-Based Single Exploration )Classic Coordinated Strategies Exploration can be speedup by means of using multiple robots, and the robots can share their perceptions and build a common map of the environmentYamauchi 1998 (Frontier-Based MRS)Integrated non-coordinated strategies Uncertainty and Map efficiency Speedup exploration time Single Exploration Integrated coordinated strategies MRS, Uncertainty
Classic non-coordinated strategiesUsing one Robot only in exploration to acquire as mush information as possible in a short time, they don’t care about localization Yamauchi 1997 (Frontier-Based Single Exploration )Classic Coordinated Strategies Exploration can be speedup by means of using multiple robots, and the robots can share their perceptions and build a common map of the environmentYamauchi 1998 (Frontier-Based MRS)Integrated non-coordinated strategies Uncertainty and Map efficiency Single Exploration Integrated coordinated strategies MRS, Uncertainty Speedup exploration time
Human in general applies the frontier based approach when entering an unknown area.First he start to gain information about the surrounding and know the obstacles positions , where he can move and the unknown areas.Then he decided to go to another Point(Frontier) where he can gain more information about the environment.And repeat this process many times till he finish exploring all the environment.