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Paper TuB01.6

Gan, Seng Keat (The University of Sydney), Fitch, Robert (University of Sydney), Sukkarieh, Salah (University of Sydney)

Real-Time Decentralized Search with Inter-Agent Collision Avoidance

Scheduled for presentation during the Regular Session "Control and Planning for UAVs" (TuB01), Tuesday, May 15, 2012, 11:45−12:00, Meeting Room 1 (Mini-sota)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on February 21, 2018

Keywords Aerial Robotics, Distributed Robot Systems

Abstract

This paper addresses the problem of coordinating a team of mobile autonomous sensor agents performing a cooperative mission while explicitly avoiding inter-agent collisions in a team negotiation process. Many multi-agent cooperative approaches disregard the potential hazards between agents, which are an important aspect to many systems and especially for airborne systems. In this work, team negotiation is performed using a decentralized gradient-based optimization approach whereas safety distance constraints are specifically designed and handled using Lagrangian multiplier methods. The novelty of our work is the demonstration of a decentralized form of inter-agent collision avoidance in the loop of the agents' real-time group mission optimization process, where the algorithm inherits the properties of performing its original mission while minimizing the probability of inter-agent collisions. Explicit constraint gradient formulation is derived and used to enhance computational advantage and solution accuracy. The effectiveness and robustness of our algorithm has been verified in a simulated environment by coordinating a team of UAVs searching for targets in a large-scale environment.

 

 

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