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A Heuristic Comparison of Optimization Algorithms for the Trajectory Planning of a 4-axis SCARA Robot Manipulator

机译:4轴围巾机器人操纵器轨迹规划优化算法的启发式比较

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This chapter presents four heuristic optimization techniques to optimize and compare the results inverse kinematics(IK)solutions, firefly, bat, particle swarm optimization(PSO)and teaching-learning-based optimization(TLBO)algorithm has been used as the optimization method for the intended purpose. In order to execute the algorithms, an objective function as the Euclidean distance between two points in space has been assigned. For each method, the convergence of the optimal position trajectory towards a set target point has been shown. The best cost plots for all algorithms have been presented. The error in positions of the obtained trajectory in X, Y and Z directions for different methods is depicted. In order to compare the outcomes of IK solutions obtained by executing the algorithms, a four-DOF SCARA robot manipulator has been considered for illustration purpose.
机译:本章提供了四种启发式优化技术来优化和比较结果逆运动学(IK)解决方案,萤火虫,蝙蝠,粒子群优化(PSO)以及基于教学的优化(TLBO)算法已被用作优化方法预期目的。为了执行算法,已经分配了作为空间中的两个点之间的欧几里德距离的目标函数。对于每个方法,已经示出了朝向设定目标点的最佳位置轨迹的收敛。已经提出了所有算法的最佳成本图。描绘了用于不同方法的X,Y和Z方向的所得轨迹的位置的误差。为了比较通过执行算法而获得的IK解决方案的结果,已经考虑了一个四-of Scara机器人操纵器以用于说明目的。

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