Real-time decentralized search with inter-agent collision avoidance
- Publication Type:
- Conference Proceeding
- Citation:
- Proceedings - IEEE International Conference on Robotics and Automation, 2012, pp. 504 - 510
- Issue Date:
- 2012-01-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| 06224975.pdf | Published version | 1.64 MB |
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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. © 2012 IEEE.
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