Trajectory generation in confined environment is crucial for wide adoption of intelligent robot manipulators. In this paper, we propose a novel motion planning approach for redundant robot arms that uses a hybrid optimization framework to search for optimal trajectories in both the configuration space and null space, generating high-quality trajectories that satisfy task constraints and collision avoidance constraints, while also avoiding local optima for incremental planners. Our approach is evaluated in an onsite polishing scenario with various robot and workpiece configurations, demonstrating significant improvements in trajectory quality compared to existing methods. The proposed approach has the potential for broad applications in industrial tasks involving redundant robot arms.

翻译：在受限环境中生成轨迹对于智能机器人操作器的广泛应用至关重要。本文提出了一种针对冗余机器人手臂的新型运动规划方法，该方法采用混合优化框架，在构型空间和零空间中同时搜索最优轨迹，生成满足任务约束和避碰约束的高质量轨迹，同时避免增量规划器陷入局部最优。本研究在包含多种机器人与工件构型的现场抛光场景中评估了所提方法，结果表明与现有方法相比，轨迹质量显著提升。该方案在涉及冗余机器人手臂的工业任务中具有广泛的应用潜力。