手动机器人轨迹规划系统:实现高效无碰撞操作

IF 5.2 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Francisco José Martínez-Peral , Jorge Borrell Méndez , Dennis Mronga , José Vicente Segura-Heras , Carlos Perez-Vidal
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引用次数: 0

摘要

装卸作业是一种非增值活动,但在许多工业过程中却是必不可少的。其中一些操作必须由双臂机器人执行,由于使用共享工作空间,这在避免碰撞方面提出了新的挑战。这项工作通过提出一个任务和运动架构(TMA)来解决这两个问题,该架构旨在优化拾取和放置任务,通过无碰撞的运动确保高效和安全的操作。该体系结构包括两个相互连接的子层,任务规划器(Task Planner, TP)和全局运动规划器(Global Motion Planner, GMP)。TP计算操作的最佳顺序,最小化总执行时间并保证无冲突的顺序。GMP使用预定义的运动策略和计算出的最优序列来规划机械臂的轨迹。这项工作提出了一种新的解决方案,通过集成相互通信的TP和MP来提高机器人在现实环境中的协调效率。仿真结果表明,提高了任务效率,减少了操作时间,并成功地避免了机器人之间的碰撞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trajectory planning system for bimanual robots: Achieving efficient collision-free manipulation
Pick-and-place operations are non-value-added activities but essential in many industrial processes. Some of these operations must be performed by dual-arm robots, which represent new challenges in terms of collision-avoidance due to the use of a shared workspace. This work addresses these two issues by proposing a Task and Motion Architecture (TMA) designed to optimize pick-and-place tasks, ensuring efficient and safe operation through collision-free movements. This architecture consists of two interconnected sublayers, the Task Planner (TP) and the Global Motion Planner (GMP). The TP calculates the optimal sequence of operations, minimizing the total execution time and guaranteeing a collision-free sequence. The GMP plans the trajectories of the robotic arms using predefined motion strategies and following the calculated optimal sequence. This work presents a novel solution for enhancing the efficiency of robot coordination in real-world settings by integrating an intercommunicated TP and MP. Results from simulations demonstrate improved task efficiency, reduced operational times, and successful collision avoidance between robots.
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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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