a decentralized architecture for multi-robot systems based ... · gianluca antonelli università...

Alessandro Marino Università degli Studi di Cassino

Gianluca Antonelli Università degli Studi di Cassino

Fabrizio Caccavale Università degli Studi della Basilicata

Lynne E. Parker University of Tennessee, Knoxville

A decentralized architecture for multi-robot systems based on the Null-Space-Behavioral control with

application to multi-robot border patrolling

Automatica.it 2011 Pisa, 7 Settembre 2011

Outline

• The border patrolling mission • Null-Space-based (NSB) behavioral approach • Centralized NSB approach to multi-robot border patrolling • Decentralized NSB approach to multi-robot border patrolling

• Simulation and experimental results

• Area patrolling (cenni) • Conclusions


A Null-space Based Behavioral Approach To Multi-Robot Patrolling

Simulation example

The Border Patrolling Mission

Patrol a border by means of one or more (semi)autonomous agents



Task function

Inverse solution

NSB 1/2 A Null-space Based Behavioral ApproachTo Multi-Robot Patrolling


Task velocity

with

with

Handling two behaviors

Any number of tasks can be handled. In the case of three tasks:

NSB 2/2 A Null-space Based Behavioral Approach To Multi-Robot Patrolling


Centralized NSB approach

Primary Task Secondary Task

Output velocities (NSB)



Decentralized Border Patrolling

Desired Goals Development and testing of a decentralized control architecture

for border patrolling such that:

Requirements

The solution has to be fully decentralized: each robot acts based only on its own sensory information The solution has to be robust vs changes in the number of teammates Collisions among robots must be avoided also in very critical conditions (high density) The algorithm has to be computationally efficient

Main Assumptions Each robot can localize itself in the environment Each robot knows the geometric description of the border Each robot has a visibility range in which it detects the presence of other agents (teammates, friends, others) Each robot has a safety range (collisions)



The same for each robotic agent

Supervisor

behaviors actions NSB

sensors actuators

Elementary behaviors Behaviors combined in more complex actions in the NSB framework The Supervisor, on the basis of sensory information, selects the action to be executed (velocity commands)

Architecture A Null-space Based Behavioral Approach To Multi-Robot Patrolling


Reach Frontier

This behavior allows the robot to reach the border along the shortest path Null space tangent to the border

Behaviors 1/3

Supervisor


sensors actuators



Clockwise (Counterclockwise) Patrol

They define the motion direction along the border Null space normal to the border

Behaviors 2/3

Supervisor


sensors actuators



Avoid (Teammate or Friend)

As a robot (blue) enters the safety area of another robot (red), a velocity command (radially directed) is generated, forcing the robot to stay on the border of the safety area The Null-space direction is tangent to the circle

Behaviors 3/3

Supervisor


sensors actuators



Action Reach Frontier

Coincides with the elementary behavior Reach Frontier Activated when the robot is far from the border: in this case, the only objective is to reach the border as soon as possible

Actions 1/4

Supervisor


sensors actuators



Action Patrol Clockwise (or Counterclockwise)

They are composed by two behaviors fully compatible in the NSB sense Forces the robot to stay on the border while moving in the clockwise or counterclockwise direction Activated to change the motion direction, when, e.g., a robot is met along the path

Actions 2/4

Supervisor


sensors actuators



Action Keep Going

Actions 3/4

Composed by two behaviors fully compatible in the NSB sense Activated to confer some unpredictability to agents patrolling behavior: based on a random variable, every T seconds the robot changes its patrolling direction

F(t,

r)

F(t,

r)

Supervisor


sensors actuators



Action Friend (or Teammate) Avoidance

Resulting path

Actions 4/4

Composed by two behaviors in general not fully compatible in the NSB sense Forces the robot (blue) to reach the frontier while avoiding another agent (black): motion along the circular border of the safety area of the agent

Supervisor


sensors actuators



Supervisor


sensors actuators

Two Supervisors: Finite State Automata: simple design (with a small number of states) Fuzzy Logic Inference System: linguistic rules to define the action selection mechanism

Supervisor 1/2

FSA FLIS



Supervisor


sensors actuators

3 macro-state {MS1, MS2, MS3} Each state associated with an action C1: border out from visibility area C2: distance from border less than a given threshold

c1: teammate in safety area c2: teammate on the left c3: teammate on the right c4: !c2 & !c3

C1

MS1: border not in the visibility area

C2

Action Reach Frontier

Action Avoid Teammate

Action Keep Going

Action Avoid Teammate

MS1: border in the visibility area

Action Patrol CW

Action Patrol CCW

Action Keep Going

MS3: robot patrolling

c1

!c1

c1

!c1

!c2

c2 !c3

c3

!C1

!C2

c4

Supervisor 2/2

Corso di Dottorato in Ingegneria Industriale e dell’Innovazione, Ciclo XXII

Finite State Automata


Simulations A large number of patrolling robots is present (green); their visibility and safety areas are assumed to be equal; friends (red) enter the border; sudden faults


Experiments and Simulations 1/7


Distance between robots


Coverage Index

Simulation without friend vehicles Simulation with friend vehicles

Distance between robots and friends

Coverage Index



Situation immediately after faults


Coverage Index

Robot Redistribution





Instantaneous Segment Idleness (ISI) = time elapsed since a border segment has been visited last time Instantaneous Border Idleness (IBI) = average over all the segments of ISI Border Idleness (BI) = average of IBI over the mission duration

IBI BI vs number of robots


The Experimental Setup

Three Pioneers 2-DX Localization achieved by means of LRF (particle filter algorithm)




Experiments

Open Border




Experiments

Closed Border




Distance from the border over time

faults

Distance between consecutive robots along the border

Experiments and Simulations 7/7 A Null-space Based Behavioral Approach To Multi-Robot Patrolling


Ongoing Work

Area Patrolling



Probabilistic approach Voronoi-based Map-based Communication required only to exchange maps key data Motion computed to increase information Handle

Spatial variability (patrol more often gates) Time-dependency (come back to visited places) Asynchronous spot visiting demand

Ongoing Work A Null-space Based Behavioral Approach To Multi-Robot Patrolling


Voronoi partitions (tessellations/diagrams): subdivisions of a set S characterized by a metric with respect to a finite number of points belonging to the set

The cells union gives back the set The cells intersections is null Computation of the cells is a decentralized algorithm

Ongoing Work A Null-space Based Behavioral Approach To Multi-Robot Patrolling


Area patrolling - experimental validation At the Laboratory of Robotics and Systems in Engineering and

Science IST, Technical University of Lisbon 3 Medusas ASVs Virtual obstacles

Greetings

Grazie e buon appetito

Fabrizio CACCAVALE Area Lab

Dipartimento di Ingegneria e Fisica dell’Ambiente

Università degli Studi della Basilicata, Italy [email protected]

www.unibas.it


mailto:[email protected]�

a decentralized architecture for multi-robot systems based ... · gianluca antonelli università...

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