基于最优传输和模型预测控制的无人系统蜂群同时任务分配和轨迹规划

IF 3.1 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xiwei Wu, Bing Xiao, Lu Cao, Haibin Huang
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引用次数: 0

摘要

本文提出了一种利用最优传输和模型预测控制(OT-MPC)同时进行无人系统蜂群任务分配和轨迹规划的方法。与传统的分层分配和规划不同,本文提出的方法同时解决任务分配和轨迹规划两个子问题。具体来说,设计了一个统一的成本函数来解决任务分配和轨迹规划问题。此外,多任务分配采用最优运输方式,根据运输成本在任务和无人系统车辆之间建立最优映射。利用模型预测控制实现轨迹规划,在考虑避障的情况下生成高质量的导航轨迹。最后,将提出的方法应用于无人水面飞行器群。通过数值模拟和实验验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Transport and Model Predictive Control-based Simultaneous Task Assignment and Trajectory Planning for Unmanned System Swarm

This paper presents a simultaneous task assignment and trajectory planning method for unmanned system swarm by using optimal transport and model predictive control (OT-MPC). Unlike the conventional hierarchical assignment and planning, the proposed approach addresses both the task assignment and trajectory planning subproblems concurrently. To be specific, a unified cost function is designed to solve task assignment and trajectory planning problem. Moreover, the multi-tasks are assigned by using optimal transport, which establishes an optimal mapping between tasks and unmanned system vehicles based on transportation cost. The trajectory planning is achieved by using model predictive control, which generates high-quality navigation trajectories considering obstacle avoidance. Finally, the proposed method is applied to the unmanned surface vehicles swarm. Numerical simulations and experiments were conducted to validate the effectiveness of the proposed method.

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来源期刊
Journal of Intelligent & Robotic Systems
Journal of Intelligent & Robotic Systems 工程技术-机器人学
CiteScore
7.00
自引率
9.10%
发文量
219
审稿时长
6 months
期刊介绍: The Journal of Intelligent and Robotic Systems bridges the gap between theory and practice in all areas of intelligent systems and robotics. It publishes original, peer reviewed contributions from initial concept and theory to prototyping to final product development and commercialization. On the theoretical side, the journal features papers focusing on intelligent systems engineering, distributed intelligence systems, multi-level systems, intelligent control, multi-robot systems, cooperation and coordination of unmanned vehicle systems, etc. On the application side, the journal emphasizes autonomous systems, industrial robotic systems, multi-robot systems, aerial vehicles, mobile robot platforms, underwater robots, sensors, sensor-fusion, and sensor-based control. Readers will also find papers on real applications of intelligent and robotic systems (e.g., mechatronics, manufacturing, biomedical, underwater, humanoid, mobile/legged robot and space applications, etc.).
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