A Model for Multi-Agent Autonomy That Uses Opinion Dynamics and Multi-Objective Behavior Optimization
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866929550310506496 |
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| author | Paine, Tyler M. Benjamin, Michael R. |
| author_facet | Paine, Tyler M. Benjamin, Michael R. |
| contents | This paper reports a new hierarchical architecture for modeling autonomous multi-robot systems (MRSs): a nonlinear dynamical opinion process is used to model high-level group choice, and multi-objective behavior optimization is used to model individual decisions. Using previously reported theoretical results, we show it is possible to design the behavior of the MRS by the selection of a relatively small set of parameters. The resulting behavior - both collective actions and individual actions - can be understood intuitively. The approach is entirely decentralized and the communication cost scales by the number of group options, not agents. We demonstrated the effectiveness of this approach using a hypothetical `explore-exploit-migrate' scenario in a two hour field demonstration with eight unmanned surface vessels (USVs). The results from our preliminary field experiment show the collective behavior is robust even with time-varying network topology and agent dropouts. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2311_11144 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | A Model for Multi-Agent Autonomy That Uses Opinion Dynamics and Multi-Objective Behavior Optimization Paine, Tyler M. Benjamin, Michael R. Robotics Multiagent Systems This paper reports a new hierarchical architecture for modeling autonomous multi-robot systems (MRSs): a nonlinear dynamical opinion process is used to model high-level group choice, and multi-objective behavior optimization is used to model individual decisions. Using previously reported theoretical results, we show it is possible to design the behavior of the MRS by the selection of a relatively small set of parameters. The resulting behavior - both collective actions and individual actions - can be understood intuitively. The approach is entirely decentralized and the communication cost scales by the number of group options, not agents. We demonstrated the effectiveness of this approach using a hypothetical `explore-exploit-migrate' scenario in a two hour field demonstration with eight unmanned surface vessels (USVs). The results from our preliminary field experiment show the collective behavior is robust even with time-varying network topology and agent dropouts. |
| title | A Model for Multi-Agent Autonomy That Uses Opinion Dynamics and Multi-Objective Behavior Optimization |
| topic | Robotics Multiagent Systems |
| url | https://arxiv.org/abs/2311.11144 |