A Dynamic Weighted Area Assignment based on a Particle Filter for Active Cooperative Perception

Jose J. Acevedo, Joao Messias, Jesus Capitan, Rodrigo Ventura, Luis Merino, and Pedro U. Lima. A Dynamic Weighted Area Assignment based on a Particle Filter for Active Cooperative Perception. IEEE Robotics and Automation Letters (RA-L), 5(2):736–743, IEEE, 2020. The contents of this paper were also selected by the ICRA'20 Program Committee for presentation at the Conference

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Abstract

This paper addresses an Active Cooperative Perception problem for Networked Robots Systems. Given a team of networked robots, the goal is finding a target using their inherent uncertain sensor data. The paper proposes a particle filter to model the probability distribution of the position of the target, which is updated using detection measurements from all robots. Then, an information-theoretic approach based on the RRT* algorithm is used to determine the optimal robots trajectories that maximize the information gain while surveying the map. Finally, a dynamic area weighted allocation approach based on particle distribution and coordination variables is proposed to coordinate the networked robots in order to cooperate efficiently in this active perception problem. Simulated and real experimental results are provided to analyze, evaluate and validate the proposed approach.

BibTeX Entry

@ARTICLE{ral20exploration,
year={2020},
issn={2377-3774},
journal={IEEE Robotics and Automation Letters (RA-L)},
volume = {5},
number = {2},
title={{A Dynamic Weighted Area Assignment based on a Particle Filter for Active Cooperative Perception}},
publisher={IEEE},
author={Jose J. Acevedo and Joao Messias and Jesus Capitan and Rodrigo Ventura and Luis Merino and Pedro U. Lima},
pages={736-743},
doi={10.1109/LRA.2020.2965876},
note={The contents of this paper were also selected by the ICRA'20 Program Committee for presentation at the Conference},
  abstract={This paper addresses an Active Cooperative Perception problem for Networked Robots Systems. Given a team of networked robots, the goal is finding a target using their inherent uncertain sensor data. The paper proposes a particle filter to model the probability distribution of the position of the target, which is updated using detection measurements from all robots. Then, an information-theoretic approach based on the RRT* algorithm is used to determine the optimal robots trajectories that maximize the information gain while surveying the map. Finally, a dynamic area weighted allocation approach based on particle distribution and coordination variables is proposed to coordinate the networked robots in order to cooperate efficiently in this active perception problem. Simulated and real experimental results are provided to analyze, evaluate and validate the proposed approach.},
}

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