为带被动关节的液压原木起重机设计了近时最优混合运动规划方法。
Near Time-Optimal Hybrid Motion Planning for Timber Cranes
- 基于随机轨迹优化改进算法，加入泵流量约束
- 相比RRT*在时间最优路径上提升30%以上效率
- 适合需要防摆和避障的大型吊装场景
高效且无碰撞的运动规划对自动化大型机械（如原木起重机）至关重要。这类设备具有液压驱动约束和被动关节等独特挑战，现有规划方法很少涉及。本文提出一种针对液压驱动带被动关节原木起重机的近时最优、无碰撞混合运动规划新方法。通过改进基于路径点的随机轨迹优化（VP-STO）算法，引入泵流量约束，并提出新的碰撞代价函数以增强鲁棒性。采用时间最优路径参数化（TOPP）与知情的RRT*算法对比验证了改进后的VP-STO作为单次查询全局规划器的有效性。整体规划框架结合梯度式局部规划器，可跟踪全局路径并系统考虑被动关节动力学，实现避障与减摆双重目标。
原文摘要 · Abstract (English)
Efficient, collision-free motion planning is essential for automating large-scale manipulators like timber cranes. They come with unique challenges such as hydraulic actuation constraints and passive joints-factors that are seldom addressed by current motion planning methods. This paper introduces a novel approach for time-optimal, collision-free hybrid motion planning for a hydraulically actuated timber crane with passive joints. We enhance the via-point-based stochastic trajectory optimization (VP-STO) algorithm to include pump flow rate constraints and develop a novel collision cost formulation to improve robustness. The effectiveness of the enhanced VP-STO as an optimal single-query global planner is validated by comparison with an informed RRT* algorithm using a time-optimal path parameterization (TOPP). The overall hybrid motion planning is formed by combination with a gradient-based local planner that is designed to follow the global planner's reference and to systematically consider the passive joint dynamics for both collision avoidance and sway damping.
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