simulation and optimization of a collaborative multi-robot heterogeneous firefighting system

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Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System Dimitrios Bakllas, Aaron Fineman and Tanay Shah 06/04/2011 ME 593 Autonomous Multi-Robot Systems

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Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System. Dimitrios Bakllas , Aaron Fineman and Tanay Shah. ME 593 Autonomous Multi-Robot Systems. 06/04/2011. Outline. Introduction Background Mapping Player-Stage Assumptions Robots Algorithm. - PowerPoint PPT Presentation

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Page 1: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting SystemDimitrios Bakllas, Aaron Fineman and Tanay Shah

06/04/2011ME 593 Autonomous Multi-Robot Systems

Page 2: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

• Introduction• Background• Mapping• Player-Stage• Assumptions• Robots• Algorithm

Outline

Page 3: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

• Distributed Firefighting• Locate Fires• Put Out Fires

• Distributed Mapping• Update Blueprint• Track Fires

Introduction

Page 4: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

• Heterogeneous swarm• Scouting Bots• Firefighting Bots

Introduction/Distributed Firefighting

http://www.toytokyo.com/shopping/index.php/page/product/product_id/5245

http://www.robot.uji.es/lab/plone/robots

Page 5: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

• Simultaneous Localization and Mapping (SLAM)• Distributed

• Mapping of the Environment• Environment is dynamic• Estimation of fire expansion

Introduction/Distributed Mapping

Page 6: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

Mapping

Standard 2D X-Y maps4D maps!

Trustworthiness of merged dataFireStored as bitmaps#RRGGBBProvides information over time

Page 7: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

Player-Stage

• Robot abstraction software• Player

– Runs on the robot– Provides a common interface to various

robots– Runs over the network

"All the world's a stage, And all the men and women merely players." - William Shakespeare, As You Like It

Page 8: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

• Stage Robot Simulator

Stage

Page 9: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

http://playerstage.sourceforge.net/

Page 10: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

http://playerstage.sourceforge.net/

Page 11: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

Player-Stage

• Gazebo– 3D version of Stage

http://playerstage.sourceforge.net/

Page 12: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

Assumptions

• The firefighting robots will be limited in number• They are heat resistant but impervious to fire and rubble• Can move easily over terrain except rubble• Firefighters are slow to due to weight of equipment• Firefighters have infinite water• All robots have infinite battery• To simulate smoky environment communication range

will be limited• Firefighters have double communication range

Page 13: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

Robots

• Scouts have standard IR sensors. Range of 20-150 cm

• They also have sonar sensors. Range of 0 to 645 cm with resolution of 2.5 cm

• SICK LIDAR sensors with field view of 360 and operating range of 10 to 2000 cm

Page 14: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

SLAM

SLAM will be used to update the preloaded map within the known environment and at the same time keep track of the current location of each individual agent.

foreach sensor in sensor types[] : foreach sensor in array[] : sensor matrix[m,n] = sensorProxy.scan[n] + normal(0, error)location = filter noise(sensor matrix[],time slice)

Page 15: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

First Come First Serve (FCFS)

With FCFS, fires will be attended to in the order they were reported.

list fire locations[]: foreach t in time : foreach robot in swarm[] : if(FOUND FIRE FLAG == True) : fire locations.add(robot.location, robot.sensor.temp)

foreach firefighter in swarm[] : if(fire locations.size > 0) goto(fire locations[1]) pop(fire locations[1])

Page 16: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

Greedy Algorithm

With the greedy algorithm, the room with the most reported fires will be attended to first.

list rooms[]while(1) : foreach robot in swarm[] : If(FOUND FIRE FLAG == True) : rooms[robot.get room()] += 1;

foreach firefighter in swarm[] : sorted rooms = rooms.sort(); if(sorted rooms[1] > 0) : goto(sorted rooms[1]) sorted rooms[1] = 0

Page 17: Simulation and Optimization of a Collaborative Multi-Robot Heterogeneous Firefighting System

Questions?