Coordinated exploration of labyrinthine Coordinated exploration of labyrinthine environments with application to the environments with application to the

“pursuit-evasion” problem“pursuit-evasion” problem

Leibniz LaboratoryLeibniz LaboratoryMagma teamMagma team

Damien Pellier – Humbert FiorinoDamien Pellier – Humbert Fiorino

{Pellier, Fiorino}@imag.fr{Pellier, Fiorino}@imag.fr

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PlanPlan

Problems tackledProblems tackled Principle of surveillance algorithmsPrinciple of surveillance algorithms A cooperative approachA cooperative approach Discussion and future prospectsDiscussion and future prospects DemonstrationDemonstration

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Problems tackledProblems tackled

« pursuit evasion » problem for mobile robots by a multi robot cooperation approach

Distributed decision Sharing robots knowledge Computing motion strategies Deliberation protocol

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Principle of Principle of surveillance algorithmssurveillance algorithms

Build a motion strategy that guarantees an intruder will be discovered by the pursuers [Suzuki 92]

Constraints on the environment

known [Yamashita 00]

unknown [Rajko 01]

1. Constraints on the robot perception

omnidirectional perception [Lavalle 97]

flash light perception [Simov 01]

1. Limits

complexity

management of robots resources

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A cooperative approach A cooperative approach PrinciplePrinciple

Algorithm for one pursuer

Assumptions

- the environment is known

- the robots have an infinite omnidirectional perception

- the intruder can have an infinite speed >> robots speed

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A cooperative approachA cooperative approachConstruction of the trajectoryConstruction of the trajectory

1st step : the critical points must be found (a critical point is an obstacle vertex that has an internal angle < 180°)

2nd step: from the critical vertices list, build the visibility graph of the environment

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3

4

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4

2

1

3

5

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A cooperative approachA cooperative approachConstruction of the trajectoryConstruction of the trajectory

3td step: the surveillance graph construction gathers all surveillance trajectories in the environment

Example from the critical point 1:

4th step: choice of the best motion strategy based upon the Dijkstra algorithm so as to compute the shortest surveillance path

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CCCNN

54321

CCNCC

54321

1, 2

NNCCN

54321

4, 5 4, 5

NNCNN

54321

CCNNN

54321

NNNNN

54321

3

1

3

1, 2 1, 2

4, 5 3

31, 2 4, 5 1, 2

3, 4, 5

N: Cleared

C: Contaminated

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A cooperative approachCooperation implementationCooperation implementation

Detection of the « delegation points »

Assistance computation The stuck robot tries to split the environment that can be monitored by independent robots

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A cooperative approach Cooperation implementationCooperation implementation

Tasks delegation: the deliberation protocol

A robot can play 4 different roles: Explorer Guard Idle robot Stuck robot

The robot’s role changes during the exploration

The deliberation protocol is based on « contracts » between the team robots

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A cooperative approach Cooperation implementationCooperation implementation

Deliberation protocol

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A cooperative approachA cooperative approach Discussion and future prospectsDiscussion and future prospects

Number of robots minimization by making them work as a team Deliberation protocol allows an efficient use of the robots resources CComputation distribution

Fault tolerance Robustness

Limitation of the critical points representation

Adaptation of the deliberation protocol for unknown environments

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DemonstrationDemonstration