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Hamiltonian coordination primitives for decentralized multiagent navigation.
- Source :
-
International Journal of Robotics Research . Sep2021, Vol. 40 Issue 10/11, p1234-1254. 21p. - Publication Year :
- 2021
-
Abstract
- We focus on decentralized navigation among multiple non-communicating agents in continuous domains without explicit traffic rules, such as sidewalks, hallways, or squares. Following collision-free motion in such domains requires effective mechanisms of multiagent behavior prediction. Although this prediction problem can be shown to be NP-hard, humans are often capable of solving it efficiently by leveraging sophisticated mechanisms of implicit coordination. Inspired by the human paradigm, we propose a novel topological formalism that explicitly models multiagent coordination. Our formalism features both geometric and algebraic descriptions enabling the use of standard gradient-based optimization techniques for trajectory generation but also symbolic inference over coordination strategies. In this article, we contribute (a) HCP (Hamiltonian Coordination Primitives), a novel multiagent trajectory-generation pipeline that accommodates spatiotemporal constraints formulated as symbolic topological specifications corresponding to a desired coordination strategy; (b) HCPnav, an online planning framework for decentralized collision avoidance that generates motion by following multiagent trajectory primitives corresponding to high-likelihood, low-cost coordination strategies. Through a series of challenging trajectory-generation experiments, we show that HCP outperforms a trajectory-optimization baseline in generating trajectories of desired topological specifications in terms of success rate and computational efficiency. Finally, through a variety of navigation experiments, we illustrate the efficacy of HCPnav in handling challenging multiagent navigation scenarios under homogeneous or heterogeneous agents across a series of environments of different geometry. [ABSTRACT FROM AUTHOR]
- Subjects :
- *TRAJECTORY optimization
*MATHEMATICAL optimization
Subjects
Details
- Language :
- English
- ISSN :
- 02783649
- Volume :
- 40
- Issue :
- 10/11
- Database :
- Academic Search Index
- Journal :
- International Journal of Robotics Research
- Publication Type :
- Academic Journal
- Accession number :
- 152807912
- Full Text :
- https://doi.org/10.1177/02783649211037731