ORIGINAL RESEARCH article
Front. Robot. AI
Sec. Robotic Control Systems
Volume 12 - 2025 | doi: 10.3389/frobt.2025.1540808
This article is part of the Research TopicAdvances in Distributed Control for Multiple RobotsView all articles
Decentralized Nonlinear Model Predictive Control-Based Flock Navigation with Real-Time Obstacle Avoidance in Unknown Obstructed Environments
Provisionally accepted
- Kyushu University, Fukuoka, Japan
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This work extends our prior work on the distributed nonlinear model predictive control (NMPC) for navigating a robot fleet following a certain flocking behavior in unknown obstructed environments with a more realistic local obstacle avoidance strategy. More specifically, we integrate the local obstacle avoidance constraint using point clouds into the NMPC framework. Here, each agent relies on data from its local sensor to perceive and respond to nearby obstacles. A point cloud processing technique is presented for both two-dimensional and three-dimensional point clouds to minimize the computational burden during the optimization. The process consists of directional filtering and down-sampling that significantly reduce the number of data points. The algorithm's performance is validated through realistic 3D simulations in Gazebo, and its practical feasibility is further explored via hardware-in-the-loop (HIL) simulations on embedded platforms.
Keywords: Nonlinear MPC, Flocking, Local obstacle avoidance, Hardware-in-the-loop, distributed control
Received: 06 Dec 2024; Accepted: 01 May 2025.
Copyright: © 2025 Gerdpratoom and Yamamoto. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Kaoru Yamamoto, Kyushu University, Fukuoka, Japan
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