【摘要】 针对通用型机器人,以运行时间最短为目标,提出一种基于自适应粒子群(APSO)时间最优轨迹规划算法。在关节空间轨迹规划中,逆解得到关节变量与时间的关系,以此建立五次多项式关节变量与时间的插值轨迹。然后,利用罚函数对其关节角度、关节速度、关节加速度进行处理,同时以插值关节各点间的时间间隔之和为优化目标,采用自适应粒子群算法进行优化求解,得到时间最优的轨迹。最后,利用MATLAB仿真软件,建立川崎FS20 N仿真模型进行验证,得到运行平稳且时间最优的运行轨迹图,仿真结果验证了该算法在轨迹规划中的可行性。更多还原

【Abstract】 Aiming at the short-term running time of general-purpose robots,a type of time optimal trajectory planning algorithm based on the Adaptive Particle Swarm Optimization(APSO) is proposed in this paper. In the joint space trajectory planning,relationship between the joint variable and time is built by the inverse solution,so as to establish the interpolation trajectory of the fifth-order polynomial joint variable and time. Then,the penalty function is used to deal with the joint angle,joint speed,and the joint acceleration; at the same time,taking the sum of time intervals between the points of the interpolated joints as the optimization goal,the adaptive particle swarm optimization algorithm is used to obtain the time-optimal trajectory.Finally,using the MATLAB simulation software to establish the Kawasaki FS20 N simulation model for verification,the running stable and time optimal operation trajectory is obtained. The simulation results verify the feasibility of the algorithm in trajectory planning.更多还原