Optimal Trajectory Planning for Robotic Manipulators Using Chicken Swarm Optimization

2016 ◽  
Author(s):  
Yu Mu ◽  
Lijuan Zhang ◽  
Xingran Chen ◽  
Xueshan Gao
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Robotic Manipulators ◽  
Swarm Optimization ◽  
Chicken Swarm Optimization ◽  
Optimal Trajectory Planning

Optimal Trajectory Generation for Robotic Manipulators Using Dynamic Programming

1987 ◽  
Vol 109 (2) ◽  
pp. 88-96 ◽  
Author(s):  
S. Singh ◽  
M. C. Leu
Keyword(s):  
Dynamic Programming ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Robotic Manipulators ◽  
Planning Algorithm ◽  
Manipulator Link ◽  
On Line ◽  
And Performance ◽  
Two Stages ◽  
Optimal Trajectory Planning

The problem of optimal control of robotic manipulators is dealt with in two stages: (1) optimal trajectory planning, which is performed off-line and results in the prescription of the position and velocity of each link as a function of time along a “given” path and (2) on-line trajectory tracking, during which the manipulator is guided along the planned trajectory using a feedback control algorithm. In order to obtain a general trajectory planning algorithm which could account for various constraints and performance indices, the technique of dynamic programming is adopted. It is shown that for a given path, this problem is reduced to a search over the velocity of one moving manipulator link. The design of the algorithm for optimal trajectory planning and the relevant computational issues are discussed. Simulations are performed to test the effectiveness of this method. The use of this algorithm in conjunction with an on-line controller is also presented.

An efficient stochastic approach for robust time-optimal trajectory planning of robotic manipulators under limited actuation

Robotica ◽  
2017 ◽  
Vol 35 (12) ◽  
pp. 2400-2417 ◽  
Author(s):  
Ming-Yong Zhao ◽  
Xiao-Shan Gao ◽  
Qiang Zhang
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Original Problem ◽  
Robotic Manipulators ◽  
Linear Optimal Control ◽  
Time Optimal ◽  
Optimal Trajectory Planning

SUMMARYThis paper focuses on the problem of robust time-optimal trajectory planning of robotic manipulators to track a given path under a probabilistic limited actuation, that is, the probability for the actuation to be limited is no less than a given bound κ. We give a general and practical method to reduce the probabilistic constraints to a set of deterministic constraints and show that the deterministic constraints are equivalent to a set of linear constraints under certain conditions. As a result, the original problem is reduced to a linear optimal control problem which can be solved with linear programming in polynomial time. In the case of κ = 1, the original problem is proved to be equivalent to the linear optimal control problem. Overall, a very general, practical, and efficient algorithm is given to solve the above problem and numerical simulation results are used to show the effectiveness of the method.

scholarly journals Optimal trajectory planning of complicated robotic timber joints based on particle swarm optimization and an adaptive genetic algorithm

2021 ◽  
Author(s):  
Yiping Meng ◽  
Yiming Sun ◽  
Wen-shao Chang
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Particle Swarm ◽  
Adaptive Genetic Algorithm ◽  
Swarm Optimization ◽  
Timber Joint ◽  
Timber Joints ◽  
Optimal Trajectory Planning

AbstractIn this paper, a methodology for path distance and time synthetic optimal trajectory planning is described in order to improve the work efficiency of a robotic chainsaw when dealing with cutting complex timber joints. To demonstrate this approach one specific complicated timber joint is used as an example. The trajectory is interpolated in the joint space by using a quantic polynomial function which enables the trajectory to be constrained in the kinematic limits of velocity, acceleration, and jerk. The particle swarm optimization (PSO) is applied to optimize the path of all cutting surfaces of the timber joint in operating space to achieve the shortest path. Based on the optimal path, an adaptive genetic algorithm (AGA) is used to optimize the time interval of interpolation points of every joint to realize the time-optimal trajectory. The results of the simulation show that the PSO method shortens the distance of the trajectory and that the AGA algorithm reduces time intervals and helps to obtain smooth trajectories, validating the effectiveness and practicability of the two proposed methodology on path and time optimization for 6-DOF robots when used in cutting tasks.

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