魏文涛, 贾文友, 江磊, 梁利东, 刘莉, 朱良恒. 能耗优化下的多移动机器人动态避撞机制[J]. 信息与控制, 2022, 51(6): 662-670. DOI: 10.13976/j.cnki.xk.2022.1510
引用本文: 魏文涛, 贾文友, 江磊, 梁利东, 刘莉, 朱良恒. 能耗优化下的多移动机器人动态避撞机制[J]. 信息与控制, 2022, 51(6): 662-670. DOI: 10.13976/j.cnki.xk.2022.1510
WEI Wentao, JIA Wenyou, JIANG Lei, LIANG Lidong, LIU Li, ZHU Liangheng. Dynamic Collision Avoidance Integrated Mechanism of Multiple Mobile Robots under Energy Consumption Optimization[J]. INFORMATION AND CONTROL, 2022, 51(6): 662-670. DOI: 10.13976/j.cnki.xk.2022.1510
Citation: WEI Wentao, JIA Wenyou, JIANG Lei, LIANG Lidong, LIU Li, ZHU Liangheng. Dynamic Collision Avoidance Integrated Mechanism of Multiple Mobile Robots under Energy Consumption Optimization[J]. INFORMATION AND CONTROL, 2022, 51(6): 662-670. DOI: 10.13976/j.cnki.xk.2022.1510

能耗优化下的多移动机器人动态避撞机制

Dynamic Collision Avoidance Integrated Mechanism of Multiple Mobile Robots under Energy Consumption Optimization

  • 摘要: 针对多移动机器人在停车避撞时能耗优化的问题,提出能耗优化下基于滚动时间窗和二叉树先序遍历的多移动机器人动态避撞(TW & BT)融合算法。基于改进A*算法求得能耗约束下的最优初始路径。依据滚动时间窗和二叉树先序遍历协同机制,以初始路径中移动机器人碰撞为触发事件,将整个作业时间轴分解为多个时间窗;在每个时间窗,以停车避撞时产生能耗最小为目标,基于二叉树先序遍历的算法求解最优避撞决策。仿真实验结果表明,一方面TW & BT融合算法具有较高的鲁棒性;另一方面对比基于动态优先级的冲突消解策略(DPS)方法,在相近的计算时间内,TW & BT融合算法实现避撞时产生能耗降低达33.1%。

     

    Abstract: To optimize the energy consumption of multiple mobile robots for parking and avoiding collisions, we propose a rolling Time Window and Binary Tree preorder traversal (TW & BT) fusion algorithm using a dynamic collision avoidance-integrated mechanism for multi-mobile robots under energy consumption optimization. First, we obtain the optimal initial paths using the improved A* algorithm. Using collision-triggered events of the optimal initial paths, we decompose the whole operation time axis into several time windows. This process minimizes the total energy consumption for parking and avoided collisions. Since one time window corresponds to one sub-problem, we obtain the optimal collision avoidance strategy using the binary tree preorder traversal method. Compared with the dynamic priority conflict resolution strategy, the simulation experimental results show that the TW & BT fusion algorithm has higher robustness, and energy consumption decreases by over 33.1% in the approximate CPU time.

     

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