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首页> 外文期刊>Robotics and Autonomous Systems >Cellular ants: A method to create collision free trajectories for a cooperative robot team
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Cellular ants: A method to create collision free trajectories for a cooperative robot team

机译:细胞蚂蚁:一种为协作机器人团队创建无碰撞轨迹的方法

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摘要

Creating collision-free trajectories for mobile robots, known as the path planning problem, is considered to be one of the basic problems in robotics. In case of multiple robotic systems, the complexity of such systems increases proportionally with the number of robots, due to the fact that all robots must act as one unit to complete one composite task, such as retaining a specific formation. The proposed path planner employs a combination of Cellular Automata (CA) and Ant Colony Optimization (ACO) techniques in order to create collision-free trajectories for every robot of a team while their formation is kept immutable. The method reacts with obstacle distribution changes and therefore can be used in dynamical or unknown environments, without the need of a priori knowledge of the space. The team is divided into subgroups and all the desired pathways are created with the combined use of a CA path planner and an ACO algorithm. In case of lack of pheromones, paths are created using the CA path planner. Compared to other methods, the proposed method can create accurate collision-free paths in real time with low complexity while the implemented system is completely autonomous. A simulation environment was created to test the effectiveness of the applied CA rules and ACO principles. Moreover, the proposed method was implemented in a system using a real world simulation environment, called Webots. The CA and ACO combined algorithm was applied to a team of multiple simulated robots without the interference of a central control. Simulation and experimental results indicate that accurate collision free paths could be created with low complexity, confirming the robustness of the method.
机译:为移动机器人创建无碰撞轨迹(称为路径规划问题)被认为是机器人技术中的基本问题之一。在多个机器人系统的情况下,由于所有机器人都必须充当一个单元来完成一项复合任务(例如保留特定的编队),因此此类系统的复杂度会随着机器人数量的增加而成比例地增加。拟议的路径规划器结合了细胞自动机(CA)和蚁群优化(ACO)技术,以便为团队中的每个机器人创建无碰撞的轨迹,同时保持其形成不变。该方法对障碍物分布变化做出反应,因此可以在动态或未知环境中使用,而无需先验空间知识。该团队分为多个子组,并结合使用CA路径规划器和ACO算法来创建所有所需路径。如果缺乏信息素,则使用CA路径规划器创建路径。与其他方法相比,该方法可以实时,准确地创建无冲突的路径,且复杂度低,而所实现的系统是完全自治的。创建了一个模拟环境,以测试所应用的CA规则和ACO原则的有效性。此外,所提出的方法是在使用真实世界仿真环境的系统(称为Webots)中实现的。 CA和ACO组合算法被应用到一个由多个模拟机器人组成的团队中,而没有中央控制的干扰。仿真和实验结果表明,可以以低复杂度创建准确的无碰撞路径,从而证实了该方法的鲁棒性。

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