北京理工大学
Beijing Institute of Technology
机器人的协同编队问题是一个综合性的研究课题，主要包括编队策略及路径规划两个阶段。针 对单一机器人在未知水下环境中执行任务时能源受限等问题，本文提出一种基于改进蚁群算法的安全域协商 捕捉策略，来解决多仿生机器人系统水下环境中对目标的协同编队捕获问题。机器人随机搜索过程中发现目 标后，利用安全域协商策略实现目标机器人周围捕获点的分配；采用改进的蚁群算法实现编队过程的路径规 划和自适应避障。在不同大小的障碍物环境中进行仿真实验，并与经典的编队策略和路径规划算法进行对比， 实验结果表明，所提出策略能够使机器人在复杂的水下障碍物环境中完成高效的协作编队捕捉任务，具备有 效性。
The collaborative formation problem of robots is a comprehensive research topic, which mainly includes two stages: formation strategy and path planning. This paper proposes a security domain negotiation capture strategy based on an improved ant colony algorithm to address the energy constraints of a single robot executing tasks in an unknown underwater environment, in order to solve the problem of collaborative formation capture of targets in multiple biomimetic robot systems in underwater environments. After discovering the target during the robot's random search process, a secure domain negotiation strategy is used to allocate capture points around the target robot; Using an improved ant colony algorithm to achieve path planning and adaptive obstacle avoidance during the formation process. Simulation experiments were conducted in obstacle environments of different sizes, and compared with classic formation strategies and path planning algorithms. The experimental results showed that the proposed strategy can enable robots to complete efficient collaborative formation capture tasks in complex underwater obstacle environments, with effectiveness.
