A distributed variable density path search and simplification method for industrial manipulators with end-effector’s attitude constraints

Abstract

In many robot operation scenarios, the end-effector’s attitude constraints of movement are indispensable for the task process, such as robotic welding, spraying, handling, and stacking. Meanwhile, the inverse kinematics, collision detection, and space search are involved in the path planning procedure under attitude constraints, making it difficult to achieve satisfactory efficiency and effectiveness in practice. To address these problems, we propose a distributed variable density path planning method with attitude constraints (DVDP-AC) for industrial robots. First, a position–attitude constraints reconstruction (PACR) approach is proposed in the inverse kinematic solution. Then, the distributed signed-distance-field (DSDF) model with single-step safety sphere (SSS) is designed to improve the efficiency of collision detection. Based on this, the variable density path search method is adopted in the Cartesian space. Furthermore, a novel forward sequential path simplification (FSPS) approach is proposed to adaptively eliminate redundant path points considering path accessibility. Finally, experimental results verify the performance and effectiveness of the proposed DVDP-AC method under end-effector’s attitude constraints, and its characteristics and advantages are demonstrated by comparison with current mainstream path planning methods.

摘要

在许多机器人操作场景中, 末端执行器的运动姿态约束是机器人完成焊接、喷涂、搬运、码垛等常见任务必不可少的。同时, 姿态约束下的路径规划过程中涉及到逆运动学、碰撞检测和空间搜索等关键问题, 在实际应用中难以兼顾令人满意的效率和约束效果。针对这些问题, 提出一种带末端约束的工业机器人分布式变密度路径规划方法(DVDP-AC)。首先, 针对运动学逆解提出位置–姿态约束重构(PACR)方法。然后, 设计了具有单步安全球(SSS)的分布式有向距离场(DSDF)模型, 以提高碰撞检测的效率。在此基础上, 在笛卡尔空间中采用变密度路径搜索方法, 并进一步提出一种考虑路径可达性的前向路径简化方法(FSPS), 以自适应地快速消除冗余的路径点。最后, 实验结果验证了所提出的DVDP-AC方法在末端执行器姿态约束下的性能和有效性, 并与目前主流路径规划方法进行比较, 说明了该方法的特点和优势。