Epistemic Prediction and Planning with Implicit Coordination for
Multi-Robot Teams in Communication Restricted Environments
- URL: http://arxiv.org/abs/2302.10393v1
- Date: Tue, 21 Feb 2023 01:52:21 GMT
- Title: Epistemic Prediction and Planning with Implicit Coordination for
Multi-Robot Teams in Communication Restricted Environments
- Authors: Lauren Bramblett, Shijie Gao, and Nicola Bezzo
- Abstract summary: In communication restricted environments, a multi-robot system can be deployed to either: i. maintain constant communication but potentially sacrifice operational efficiency due to proximity constraints or ii. allow disconnections to increase environmental coverage efficiency, challenges on how, when, and where to reconnect (rendezvous problem)
This paper proposes a coordinated prediction and planning framework to achieve consensus without communicating for exploration and coverage, task discovery and completion, and rendezvous applications.
- Score: 2.781492199939609
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In communication restricted environments, a multi-robot system can be
deployed to either: i) maintain constant communication but potentially
sacrifice operational efficiency due to proximity constraints or ii) allow
disconnections to increase environmental coverage efficiency, challenges on
how, when, and where to reconnect (rendezvous problem). In this work we tackle
the latter problem and notice that most state-of-the-art methods assume that
robots will be able to execute a predetermined plan; however system failures
and changes in environmental conditions can cause the robots to deviate from
the plan with cascading effects across the multi-robot system. This paper
proposes a coordinated epistemic prediction and planning framework to achieve
consensus without communicating for exploration and coverage, task discovery
and completion, and rendezvous applications. Dynamic epistemic logic is the
principal component implemented to allow robots to propagate belief states and
empathize with other agents. Propagation of belief states and subsequent
coverage of the environment is achieved via a frontier-based method within an
artificial physics-based framework. The proposed framework is validated with
both simulations and experiments with unmanned ground vehicles in various
cluttered environments.
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