Distributed Search Planning in 3-D Environments With a Dynamically Varying Number of Agents
Abstract
In this work, a novel distributed search-planning framework is proposed, where a dynamically varying team of autonomous agents cooperate in order to search multiple objects of interest in three-dimension (3-D). It is assumed that the agents can enter and exit the mission space at any point in time, and as a result the number of agents that actively participate in the mission varies over time. The proposed distributed search-planning framework takes into account the agent dynamical and sensing model, and the dynamically varying number of agents, and utilizes model predictive control (MPC) to generate cooperative search trajectories over a finite rolling planning horizon. This enables the agents to adapt their decisions on-line while considering the plans of their peers, maximizing their search planning performance, and reducing the duplication of work.
Keywords
Cite
@article{arxiv.2304.08932,
title = {Distributed Search Planning in 3-D Environments With a Dynamically Varying Number of Agents},
author = {Savvas Papaioannou and Panayiotis Kolios and Theocharis Theocharides and Christos G. Panayiotou and Marios M. Polycarpou},
journal= {arXiv preprint arXiv:2304.08932},
year = {2023}
}
Comments
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023