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首页> 外文期刊>IEEE Transactions on Robotics and Automation >Motion planning of multiple mobile robots for Cooperative manipulation and transportation
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Motion planning of multiple mobile robots for Cooperative manipulation and transportation

机译:用于协作操纵和运输的多个移动机器人的运动计划

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In this paper, we propose a motion-planning method of multiple mobile robots for cooperative transportation of a large object in a three-dimensional environment. This task has various kinds of problems, such as obstacle avoidance and stable manipulation. All of these problems cannot be solved at once, since it would result in a dramatic increase of the computational time. Accordingly, we divided the motion planner into a global path planner and a local manipulation planner, designed them, and integrated them. The aim was to integrate a gross motion planner and a fine motion planner. Concerning the global path planner, we reduced the dimensions of the configuration space (C-space) using the feature of transportation by mobile robots. We used the potential field to find the solution by searching in this smaller-dimension reconstructed C-space. In the global path planner, the constraints of the object manipulation are considered as the cost function and the heuristic function in the A/sup */ search. For the local manipulation planner, we developed a manipulation technique, which is suitable for mobile robots by position control. We computed the conditions in which the object becomes unstable during manipulation and generated each robot's motion, considering the robots' motion errors and indefinite factors from the planning stage. We verified the effectiveness of our proposed motion planning method through simulations.
机译:在本文中,我们提出了一种用于在三维环境中协同运输大型物体的多个移动机器人的运动计划方法。该任务具有各种问题,例如避障和稳定操纵。所有这些问题不能立即解决,因为这将导致计算时间的急剧增加。因此,我们将运动计划器分为全局路径计划器和局部操纵计划器,对其进行设计和集成。目的是将总体运动计划程序和精细运动计划程序集成在一起。关于全局路径规划器,我们使用了移动机器人的运输功能来减小了配置空间(C空间)的尺寸。我们使用势场通过在较小尺寸的重构C空间中搜索来找到解决方案。在全局路径规划器中,对象操作的约束被视为A / sup * /搜索中的成本函数和启发式函数。对于本地操纵计划者,我们开发了一种操纵技术,该技术适用于通过位置控制的移动机器人。考虑到机器人的运动误差和规划阶段的不确定因素,我们计算了在操纵过程中物体变得不稳定的条件,并生成了每个机器人的运动。我们通过仿真验证了我们提出的运动计划方法的有效性。

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