Abstract
We introduce the problem of navigating a group of robots having prioritized formations amidst static and dynamic obstacles. Our formulation allows users to define a number of template formations, each with a specified priority value. At each planning cycle, we compute a new formation which accounts for both these priority values and the safe progress of the robots towards their goal. To this end, we introduce a new velocity-based navigation approach which we denote as Formation Velocity Obstacles (FVO). Like other velocity-based approaches, FVO allows anticipatory collision avoidance accounting for the likely future motion of nearby obstacles. However, we extend these previous approaches and allow anisotropic agents which rotate themselves to orient along their direction of travel. We integrate these FVOs with a Bayesian framework to infer priority values for arbitrary formations from the user-given templates. The result is a complete framework for prioritized formation planning.
Original language | English (US) |
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Article number | 7140038 |
Pages (from-to) | 5983-5989 |
Number of pages | 7 |
Journal | Proceedings - IEEE International Conference on Robotics and Automation |
Volume | 2015-June |
Issue number | June |
DOIs | |
State | Published - Jun 29 2015 |
Event | 2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States Duration: May 26 2015 → May 30 2015 |