Cooperating AmigoBots Framework and Algorithms

Slides:



Advertisements
Similar presentations
January 8, 2008Spark Robotics RISE08 DIOS – A Distributed Intelligent Operating Schema Dr. Reuven Granot and Chad Trytten Spark Robotics Inc.
Advertisements

Robot Motion Planning: Approaches and Research Issues
School of Systems, Engineering, University of Reading rkala.99k.org April, 2013 Motion Planning for Multiple Autonomous Vehicles Rahul Kala Literature.
DESIGN OF A GENERIC PATH PATH PLANNING SYSTEM AILAB Path Planning Workgroup.
Mobile – robot remote control and communication system design P. Petrova, R. Zahariev Central Laboratory of Mechatronics and Instrumentation Bulgarian.
Zach Ramaekers Computer Science University of Nebraska at Omaha Advisor: Dr. Raj Dasgupta 1.
ECE 4340/7340 Exam #2 Review Winter Sensing and Perception CMUcam and image representation (RGB, YUV) Percept; logical sensors Logical redundancy.
Experiences with an Architecture for Intelligent Reactive Agents By R. Peter Bonasso, R. James Firby, Erann Gat, David Kortenkamp, David P Miller, Marc.
Automatic Control & Systems Engineering Autonomous Systems Research Mini-UAV for Urban Environments Autonomous Control of Multi-UAV Platforms Future uninhabited.
A Free Market Architecture for Distributed Control of a Multirobot System The Robotics Institute Carnegie Mellon University M. Bernardine Dias Tony Stentz.
Monte Carlo Localization
Field Navigational GPS Robot Final Presentation & Review Chris Foley, Kris Horn, Richard Neil Pittman, Michael Willis.
Particle Filters for Mobile Robot Localization 11/24/2006 Aliakbar Gorji Roborics Instructor: Dr. Shiri Amirkabir University of Technology.
An experiment on squad navigation of human and robots IARP/EURON Workshop on Robotics for Risky Interventions and Environmental Surveillance January 7th-8th,
Robotics for Intelligent Environments
Simultaneous Localization and Map Building System for Prototype Mars Rover CECS 398 Capstone Design I October 24, 2001.
Behavior- Based Approaches Behavior- Based Approaches.
Distributed Robot Agent Brent Dingle Marco A. Morales.
Tennessee State University College of Engineering ENGINEERING RESEARCH INSTITUTE (ERI) Interdisciplinary Research in Robotics Intelligent Tactical Mobility.
Architectural Design Establishing the overall structure of a software system Objectives To introduce architectural design and to discuss its importance.
Robots at Work Dr Gerard McKee Active Robotics Laboratory School of Systems Engineering The University of Reading, UK
What is it? A mobile robotics system controls a manned or partially manned vehicle-car, submarine, space vehicle | Website for Students.
June 12, 2001 Jeong-Su Han An Autonomous Vehicle for People with Motor Disabilities by G. Bourhis, O.Horn, O.Habert and A. Pruski Paper Review.
Fuzzy control of a mobile robot Implementation using a MATLAB-based rapid prototyping system.
Zereik E., Biggio A., Merlo A. and Casalino G. EUCASS 2011 – 4-8 July, St. Petersburg, Russia.
Autonomous Surface Navigation Platform Michael Baxter Angel Berrocal Brandon Groff.
UBSwarm: Design of a Software Environment to Deploy Multiple Decentralized Robots Tamer Abukhalil, Madhav Patil, Advisor: Prof. Tarek Sobh Robotics, Intelligent.
Teaching Deliberative Navigation Using the LEGO RCX and Standard LEGO Components Gary R. Mayer, Dr. Jerry Weinberg, Dr. Xudong Yu
Nuttapon Boonpinon Advisor Dr. Attawith Sudsang Department of Computer Engineering,Chulalongkorn University Pattern Formation for Heterogeneous.
Joint International Master Project Dennis Böck & Dirk C. Aumueller 1.
Flakey Flakey's BackFlakey's Front. Flakey's Control Architecture The following is cited from the SRI web pages: Overview SRI's mobile robot, Flakey,
Multiple Autonomous Ground/Air Robot Coordination Exploration of AI techniques for implementing incremental learning. Development of a robot controller.
Intelligent Mobile Robotics Czech Technical University in Prague Libor Přeučil
Robot Autonomous Perception Model For Internet-Based Intelligent Robotic System By Sriram Sunnam.
Leslie Luyt Supervisor: Dr. Karen Bradshaw 2 November 2009.
Monitoring, Modelling, and Predicting with Real-Time Control Dr Ian Oppermann Director, CSIRO ICT Centre.
DARPA TMR Program Collaborative Mobile Robots for High-Risk Urban Missions Third Quarterly IPR Meeting May 11, 1999 P. I.s: Leonidas J. Guibas and Jean-Claude.
Chapter 40 Springer Handbook of Robotics, ©2008 Presented by:Shawn Kristek.
Disturbed Behaviour in Co-operating Autonomous Robots Robert Ghanea-Hercock & David Barnes Salford University, England.
Mobile Robot Navigation Using Fuzzy logic Controller
Boundary Assertion in Behavior-Based Robotics Stephen Cohorn - Dept. of Math, Physics & Engineering, Tarleton State University Mentor: Dr. Mircea Agapie.
DISTRIBUTED COMPUTING Introduction Dr. Yingwu Zhu.
1 Distributed and Optimal Motion Planning for Multiple Mobile Robots Yi Guo and Lynne Parker Center for Engineering Science Advanced Research Computer.
A Multidisciplinary Approach for Using Robotics in Engineering Education Jerry Weinberg Gary Mayer Department of Computer Science Southern Illinois University.
Recharging Process 1.Robot detects low battery 2.Robot requests a bay from the charging station over wireless 3.Charging station accepts or denies the.
1 Structure of Aalborg University Welcome to Aalborg University.
Riga Technical University Department of System Theory and Design Usage of Multi-Agent Paradigm in Multi-Robot Systems Integration Assistant professor Egons.
Introduction to Artificial Intelligence CS 438 Spring 2008 Today –AIMA, Ch. 25 –Robotics Thursday –Robotics continued Home Work due next Tuesday –Ch. 13:
Abstract A Structured Approach for Modular Design: A Plug and Play Middleware for Sensory Modules, Actuation Platforms, Task Descriptions and Implementations.
Behavior-based Multirobot Architectures. Why Behavior Based Control for Multi-Robot Teams? Multi-Robot control naturally grew out of single robot control.
CIS 2011 rkala.99k.org 1 st September, 2011 Planning of Multiple Autonomous Vehicles using RRT Rahul Kala, Kevin Warwick Publication of paper: R. Kala,
Ghislain Fouodji Tasse Supervisor: Dr. Karen Bradshaw Computer Science Department Rhodes University 24 March 2009.
Towards the autonomous navigation of intelligent robots for risky interventions Janusz Bedkowski, Grzegorz Kowalski, Zbigniew Borkowicz, Andrzej Masłowski.
Abstract Each July, the Association for Unmanned Vehicle Systems International holds an annual International Aerial Robotics Competition (IARC), with major.
Lynton Dicks Supervisor: Karen Bradshaw CO-OPERATIVE MAPPING AND LOCALIZATION OF AUTONOMOUS ROBOTS.
Ghislain Fouodji Tasse Supervisor: Dr. Karen Bradshaw Computer Science Department Rhodes University 04 August 2009.
Dynamic Mission Planning for Multiple Mobile Robots Barry Brumitt and Anthony Stentz 26 Oct, 1999 AMRS-99 Class Presentation Brian Chemel.
Constraint-Based Motion Planning for Multiple Agents Luv Kohli COMP259 March 5, 2003.
Autonomy: Executive and Instruments Life in the Atacama 2004 Science & Technology Workshop Nicola Muscettola NASA Ames Reid Simmons Carnegie Mellon.
Robot Vision SS 2009 Matthias Rüther ROBOT VISION 2VO 1KU Matthias Rüther.
Basilio Bona DAUIN – Politecnico di Torino
University of Pennsylvania 1 GRASP Control of Multiple Autonomous Robot Systems Vijay Kumar Camillo Taylor Aveek Das Guilherme Pereira John Spletzer GRASP.
Multi-robot
ISTC-CNR contribution to D2.2
Alexis Maldonado & Georg Bartels
Automation as the Subject of Mechanical Engineer’s interest
TOWARDS A DESIRED TRANSPORT FUTURE: SAFE, SUFFICIENT AND AFFORDABLE
Robot Teams Topics: Teamwork and Its Challenges
Mobile Robots Automated Guided Vehicles (AGVs) Autonomous Planes
SENSOR BASED CONTROL OF AUTONOMOUS ROBOTS
Presentation transcript:

Cooperating AmigoBots Framework and Algorithms Anustup Choudhury Dheren Gala Jasraj Dange Harish Rajamani B.E. Computers(D-17)

An Example in Autonomy NUCLEAR POWER PLANT MANIPULATION monitoring and mapping areas handling and inspecting materials repair and maintenance WHY AUTOMATION? Safety Accuracy Efficiency

An Example in Autonomy Functions The Physical World Perception Action Cognition Functions Perception Vision Action Motion Manipulation Cognition 3 Level Programming Support

An Example in Cooperation Foraging in Hazardous Environments Controlled pushing of large objects Speed of operation Fault tolerance Functional decomposition

LITERATURE SURVEY Single Robot Systems Multi-Robot Systems Robot Motion Planning Localization Multi-Robot Systems Test-beds Communication structures Architectures

SINGLE ROBOT SYSTEMS Robot motion planning Types of control Deliberative Reactive Hybrid

Robot motion planning-Deliberative control Known Environments Basic Path Planner 1 Free space generation 2 Model building 3 Solution path searching Eg. Voronoi Diagrams

Robot motion planning- Reactive control Unknown Environments Cognition Modeling Implicit Rules E.g. Fuzzy Control

Robot motion planning-Hybrid control Statistical Techniques Dynamic Environments Global path- initially Local modifications- during runtime Randomized techniques High dimensional spaces Randomized “milestones” E.g. RRT Algorithm

Localization Accurate position estimation Types Examples Relative position methods Absolute position methods Examples Odometry Inertial Navigation Triangulation Landmark Recognition Markov techinique

MULTIPLE ROBOT SYSTEMS Multiplicity- Just another layer! Canonical Task Domains Traffic Control Box Pushing Exploration Foraging Formation and Marching

MULTIPLE ROBOT SYSTEMS Communication Structures Interaction via Environment Interaction via Sensing Interaction via Communication Group Architectures- Issues Centralization or Decentralization? Homogeneous or Heterogeneous?

DESIGN Design of Architecture Design of Robot Design of Software

DESIGN-ARCHITECTURE Centralized Architecture Homogeneous Robots

DESIGN- ROBOT Physical Differential drive Holonomic Motion Sensorial Input Odometer

DESIGN- ROBOT Microcontroller Operating system Modules Communication Obstacle avoidance

DESIGN- SOFTWARE Control architecture System architecture Communication Application Program Interface Modules Motion planning Sensor interpreting routines Localization routines Multi-robot interface

IMPLEMENTATION AmigoBot AmigOS ARIA Saphira Tools

IMPLEMENTATION- AmigoBot Onboard Microcontroller (H8) Range Finding Capability Differential Drive Shaft Encoder Communication Capability Nearly Holonomic

IMPLEMENTATION- AmigOS Low Level Support for hardware “Open Technology” Client Server Architecture Self Sufficient for Autonomous operation

Saphira/ARIA- System Architecture Micro-tasking OS User Routines Communications Interface State Reflector

Saphira/ARIA-Control Architecture ARIA-Basic elements of action Saphira- Higher level routines Colbert Development Environment

IMPLEMENTATION- TOOLS AmigoMAPPER A-Priori map generation AmigoEYES In-built Simulator and Robot connection capability Highest-level of abstraction Graphical Interface for accepting basic commandsStopped

PROPOSED APPLICATIONS Navigation in hazardous areas Intelligent Escorts Cargo-Manipulation in Shipping Non-Intelligent Human Tasks

ACKNOWLEDGEMENTS Mr. Kalapathy G. Balakrishnan DR. Prabir K. Pal Project Advisor DR. Prabir K. Pal Department of Remote Handling and Robotics (B.A.R.C) DR. Manjit Singh Head of Department, Department of Remote Handling and Robotics (B.A.R.C)

Thank You