提出改进的几何迭代法,高效解决浮动基软体机器人的运动规划问题。
Geometric Iterative Approach for Efficient Inverse Kinematics and Planning of Continuum Robots with a Floating Base Under Environment Constraints
- 采用两层几何迭代策略,消除初始形态依赖
- 末端位置偏差约4mm,姿态误差≤1度,迭代次数减少127.4次
- 适合医疗手术、狭小空间作业等需高精度柔性机器人场景
具有浮动基的连续体机器人在医疗手术和设备维护等狭小空间中表现出优异操作能力,但低成本的运动与规划解决方案仍面临挑战。本文研究几何迭代策略在连续体机器人中的应用,提出基于改进双层几何迭代策略的运动规划算法。首先,深入分析多段肌腱驱动连续体机器人在浮动基下的运动学特性与有效工作空间;随后,针对现有方法在连续体机器人中对初始臂形依赖的问题,提出通用化迭代算法。进一步将任务扩展至考虑环境因素的跟随领航任务,并提出相应扩展算法。仿真对比表明,所提方法有效消除初始形态依赖,显著提升求解效率与精度。实验结果验证了该方法在浮动基连续体机器人运动规划中的可行性:末端位置平均偏差约4 mm,姿态平均偏差不超过1度,相比同类方法平均迭代次数减少127.4次,时间成本降低72.6 ms。
原文摘要 · Abstract (English)
Continuum robots with floating bases demonstrate exceptional operational capabilities in confined spaces, such as those encountered in medical surgeries and equipment maintenance. However, developing low-cost solutions for their motion and planning problems remains a significant challenge in this field. This paper investigates the application of geometric iterative strategy methods to continuum robots, and proposes the algorithm based on an improved two-layer geometric iterative strategy for motion planning. First, we thoroughly study the kinematics and effective workspace of a multi-segment tendon-driven continuum robot with a floating base. Then, generalized iterative algorithms for solving arbitrary-segment continuum robots are proposed based on a series of problems such as initial arm shape dependence exhibited by similar methods when applied to continuum robots. Further, the task scenario is extended to a follow-the-leader task considering environmental factors, and further extended algorithm are proposed. Simulation comparison results with similar methods demonstrate the effectiveness of the proposed method in eliminating the initial arm shape dependence and improving the solution efficiency and accuracy. The experimental results further demonstrate that the method based on improved two-layer geometric iteration can be used for motion planning task of a continuum robot with a floating base, under an average deviation of about 4 mm in the end position, an average orientation deviation of no more than 1 degree, and the reduction of average number of iterations and time cost is 127.4 iterations and 72.6 ms compared with similar methods, respectively.
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