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为了更好地适应家庭环境下的人机交互,设计了一款可根据任务需求相应调整连杆形状的四关节可变形操作臂.与传统刚性臂相比,可变形臂具有灵巧度高、成本低和本质安全等优势,但臂形的任意性也会给操作臂运动学逆解带来额外的困难.针对可变形臂的空间点触任务,本文通过引入“点触角”这一概念放松了末端执行器的姿态约束,从而使原本欠驱动的运动学逆解问题转化为了在满足点触位置约束下,以点触角最小为优化目标的冗余臂逆解优化问题.针对该问题的求解耗时和点触精度,在旋量模型的基础上分别提出了改进的序列二次规划法(SQP)和粒子群优化(PSO)与Paden-Kahan(PSO-PK)子问题混合算法.SQP方法直接在位置层面进行非线性最优化问题求解,实验结果显示该方法在臂形由特殊变为任意时求解耗时几乎不会增加,求解效率高,对可变形臂的在线实时控制具有一定意义;同时利用分层搜索法进行初值设定可以降低该算法陷入局部极值的概率.PSO-PK算法利用Paden-Kahan子问题法的解析逆解对粒子群优化算法进行降维,实验结果表明,该算法能够在保证点触位置无误差的情况下获得稳定的最小点触角,从而使点触性能得到提高.
In order to better adapt to the human-computer interaction in the home environment, a four-joint deformable manipulator is designed which can adjust the shape of the connecting rod according to the task demand.Compared with the traditional rigid arm, the deformable arm has dexterity and high cost Low and intrinsically safe, but arm’s arbitrariness also brings additional difficulties to the kinematic inverse of the manipulator.For the space touch task of the deformable arm, by introducing the concept of “contact angle ” The attitude constraint of the end effector is relaxed, so that the under-actuated kinematic inverse problem is transformed into the redundant-arm inverse solution optimization problem with the minimum point-of-contact angle as the optimization objective under the constraint of the touch point position. The time-consuming and the precision of the touch points are solved. Based on the spin-spin model, an improved Hybrid Sequential Quadratic Programming (SQP) and Particle Swarm Optimization (PSO) and Paden-Kahan (PSO- The method directly solves the nonlinear optimization problem at the position level. The experimental results show that this method can hardly solve the time-consuming problem when the arm shape is changed from special to arbitrary, and has the advantages of high solution efficiency and real-time control of the deformable arm. Meanwhile using the stratified search method to set the initial value can reduce the probability of the algorithm falling into local extremum.PSO-PK algorithm uses the analytical inverse solution of the Paden-Kahan sub-problem method to reduce the particle swarm optimization algorithm, the experimental results The results show that the algorithm can obtain the stable minimum contact angle without any error in the touch position, and improve the touch performance.