在未知环境下基于模糊预测的力/位混合控制方法

针对机器人在形状未知的接触环境表面上进行柔顺力控制的问题,在传统的力/位混合控制模型中采用一种模糊预测算法.此算法利用机械手末端与环境已产生的接触轨迹和运动方向,通过三种预测因子(满意度因子,曲率适应因子,参考比例因子),预测并调整未来采样时刻的力/位混合控制模型中的期望轨迹.每次预测时首先对以前的预测进行评估,同时考虑环境曲率和刚度变化的特点.此预测算法还可以应用于阻抗控制模型中.仿真证明,这种方法可以在不同的控制模型中取得较好的力控制效果,对未知环境的变化具有较强的适应能力.

Position/Force Control Based on Fuzzy Prediction in Unknown Environment

A fuzzy prediction algorithm arising from conventional hybrid position/force control model is developed to deal with a force-controlled execution of compliant robot tasks in an unknown environment.According to the known contacting path of the manipulator's end effector and its motional direction,the algorithm makes use of the three prediction factors(satisfiability,curvature adaptability and reference proportion) to predict and readjust the desired trajectory given in hybrid position/force control model when sampling in future.The last prediction shall be re-evaluated first once a prediction starts and,at the same time,the environmental change in curvature and stiffness should be taken into account.The algorithm is also available to be applied to impedance control model.The simulation results verify that the proposed fuzzy prediction will result in better force control in different control models and has high adaptability to unknown environment in changing.