基于离散化的六足机器人自由步态规划

为精细模仿生物步态,充分发挥六足机器人运动潜能,本文在离散化机器人足端轨迹的基础上,融合中枢模式发生器(central pattern generator,CPG)模型与反射模型的核心思想,建立了离散化步态模型,结合稳定性分析,构建了机器人稳定的位置状态空间,将复杂的步态规划问题转化为稳定的位置状态空间中位置状态间的排序问题,在此基础上,提出了一种新的自由步态生成算法,并基于平均稳定裕量对该算法进行了优化.样机步态实验结果表明,自由步态生成算法与自由步态优化算法均可生成在一定程度上符合生物运动特点的稳定步态,实现机器人运动过程中速度的动态调整,跨越宽度为步距的障碍,且基于平均稳定裕量的自由步态优化算法生成步态的稳定性要远大于自由步态生成算法.

Free gait planning for a hexapod robot based on discretization

In order to precisely imitate biological gait and give full play to the potential of hexapod robots, we build a discrete model of stepping based on the discretization of foot trajectories and the fusion of central-pattern-generation (CPG) model and the reflect model. Based on the stability analysis, a stable state-space is constructed and the issue of gait planning is transformed into the sequencing problem of states in the stable state-space. Then, a new free gait generation algorithm is proposed and it is optimized based on the average stability margin. The gait experiment results of the prototype show that both the free gait generation algorithm and the optimized algorithm can generate stable gaits which accord with movement characteristics of creatures in adjusting the speed dynamically during the moving process and in bypassing the obstacle with width up to the stroke length. By comparing the results, we find that the gait generated by the optimized free gait generation algorithm is more stable than that generated by the free gait generation algorithm.