多机器人协作系统的任务分配与路径规划算法研究
摘要
多机器人协作系统在现代工业、物流和救援等领域具有重要应用价值，其核心问题之一是任务分配与路径规划的高效协同。本研究针对多机器人系统中任务分配效率低、路径冲突频繁的问题，提出了一种基于分布式优化的任务分配与路径规划联合算法。该算法通过引入优先级动态调整机制，在保证全局任务最优分配的同时，显著降低了局部路径冲突概率。研究采用改进的拍卖算法实现任务分配，并结合A*算法进行路径规划，同时设计了冲突检测与解决模块以提升系统运行效率。实验结果表明，所提算法在复杂环境下能够有效减少任务完成时间，提高路径规划的成功率，相较于传统方法平均性能提升约25%。此外，本研究还提出了一种评价多机器人协作效率的综合指标体系，为后续研究提供了参考框架。主要创新点包括：提出了融合任务分配与路径规划的联合优化策略，设计了适用于动态环境的冲突解决机制，并建立了多维度性能评估模型。研究成果为多机器人系统的实际应用提供了理论支持和技术保障，具有较高的实用性和推广价值。
关键词：多机器人协作；任务分配与路径规划；分布式优化
Abstract
Multi-robot collaborative systems play a crucial role in modern industries, logistics, and rescue operations, with task allocation and path planning being one of their core challenges for efficient coordination. This study addresses the issues of low task allocation efficiency and frequent path conflicts in multi-robot systems by proposing a joint algorithm based on distributed optimization for task allocation and path planning. By incorporating a dynamic priority adjustment mechanism, the algorithm ensures globally optimal task allocation while significantly reducing the probability of local path conflicts. The improved auction algorithm is employed for task allocation, combined with the A* algorithm for path planning, and a conflict detection and resolution module is designed to enhance system operational efficiency. Experimental results demonstrate that the proposed algorithm effectively reduces task completion time and improves the success rate of path planning in complex environments, achieving an average performance improvement of approximately 25% compared to traditional methods. Furthermore, this study introduces a comprehensive indicator system for evaluating the collaborative efficiency of multi-robot systems, providing a reference fr amework for future research. Key innovations include the development of a joint optimization strategy integrating task allocation and path planning, the design of a conflict resolution mechanism adaptable to dynamic environments, and the establishment of a multi-dimensional performance evaluation model. These findings offer theoretical support and technical assurance for the practical application of multi-robot systems, showcasing high applicability and promotion value.
Keywords：Multi-Robot Collaboration; Task Allocation And Path Planning; Distributed Optimization
目 录
摘要 I
Abstract II
一、绪论 1
(一) 多机器人协作系统的研究背景与意义 1
(二) 任务分配与路径规划的研究现状分析 1
(三) 本文研究方法与技术路线 2
二、多机器人任务分配算法研究 2
(一) 任务分配的基本理论与模型构建 2
(二) 基于优化算法的任务分配策略设计 3
(三) 分布式任务分配机制的实现与验证 3
三、多机器人路径规划算法研究 4
(一) 路径规划的核心问题与挑战 4
(二) 动态环境下的路径规划算法设计 5
(三) 避障与效率兼顾的路径优化方法 5
四、协作系统的综合算法设计与实验验证 6
(一) 协作系统中任务分配与路径规划的集成 6
(二) 算法性能评估指标体系构建 7
(三) 实验验证与结果分析 7
结 论 9
参考文献 10
摘要
多机器人协作系统在现代工业、物流和救援等领域具有重要应用价值，其核心问题之一是任务分配与路径规划的高效协同。本研究针对多机器人系统中任务分配效率低、路径冲突频繁的问题，提出了一种基于分布式优化的任务分配与路径规划联合算法。该算法通过引入优先级动态调整机制，在保证全局任务最优分配的同时，显著降低了局部路径冲突概率。研究采用改进的拍卖算法实现任务分配，并结合A*算法进行路径规划，同时设计了冲突检测与解决模块以提升系统运行效率。实验结果表明，所提算法在复杂环境下能够有效减少任务完成时间，提高路径规划的成功率，相较于传统方法平均性能提升约25%。此外，本研究还提出了一种评价多机器人协作效率的综合指标体系，为后续研究提供了参考框架。主要创新点包括：提出了融合任务分配与路径规划的联合优化策略，设计了适用于动态环境的冲突解决机制，并建立了多维度性能评估模型。研究成果为多机器人系统的实际应用提供了理论支持和技术保障，具有较高的实用性和推广价值。
关键词：多机器人协作；任务分配与路径规划；分布式优化
Abstract
Multi-robot collaborative systems play a crucial role in modern industries, logistics, and rescue operations, with task allocation and path planning being one of their core challenges for efficient coordination. This study addresses the issues of low task allocation efficiency and frequent path conflicts in multi-robot systems by proposing a joint algorithm based on distributed optimization for task allocation and path planning. By incorporating a dynamic priority adjustment mechanism, the algorithm ensures globally optimal task allocation while significantly reducing the probability of local path conflicts. The improved auction algorithm is employed for task allocation, combined with the A* algorithm for path planning, and a conflict detection and resolution module is designed to enhance system operational efficiency. Experimental results demonstrate that the proposed algorithm effectively reduces task completion time and improves the success rate of path planning in complex environments, achieving an average performance improvement of approximately 25% compared to traditional methods. Furthermore, this study introduces a comprehensive indicator system for evaluating the collaborative efficiency of multi-robot systems, providing a reference fr amework for future research. Key innovations include the development of a joint optimization strategy integrating task allocation and path planning, the design of a conflict resolution mechanism adaptable to dynamic environments, and the establishment of a multi-dimensional performance evaluation model. These findings offer theoretical support and technical assurance for the practical application of multi-robot systems, showcasing high applicability and promotion value.
Keywords：Multi-Robot Collaboration; Task Allocation And Path Planning; Distributed Optimization
目 录
摘要 I
Abstract II
一、绪论 1
(一) 多机器人协作系统的研究背景与意义 1
(二) 任务分配与路径规划的研究现状分析 1
(三) 本文研究方法与技术路线 2
二、多机器人任务分配算法研究 2
(一) 任务分配的基本理论与模型构建 2
(二) 基于优化算法的任务分配策略设计 3
(三) 分布式任务分配机制的实现与验证 3
三、多机器人路径规划算法研究 4
(一) 路径规划的核心问题与挑战 4
(二) 动态环境下的路径规划算法设计 5
(三) 避障与效率兼顾的路径优化方法 5
四、协作系统的综合算法设计与实验验证 6
(一) 协作系统中任务分配与路径规划的集成 6
(二) 算法性能评估指标体系构建 7
(三) 实验验证与结果分析 7
结 论 9
参考文献 10
