scholarly journals Online Time-Optimal Trajectory Planning for Robotic Manipulators Using Adaptive Elite Genetic Algorithm With Singularity Avoidance

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 146301-146308 ◽  
Author(s):  
Yi Liu ◽  
Chen Guo ◽  
Yongpeng Weng
Keyword(s):  
Genetic Algorithm ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Robotic Manipulators ◽  
Singularity Avoidance ◽  
Time Optimal ◽  
Optimal Trajectory Planning

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 A Dual-Thread Method for Time-Optimal Trajectory Planning in Joint Space Based on Improved NGA

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Kaipeng Zhang ◽  
Ning Liu ◽  
Gao Wang
Keyword(s):  
Genetic Algorithm ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Joint Space ◽  
Time Saving ◽  
Expected Time ◽  
Fitness Sharing ◽  
Elite Strategy ◽  
Time Optimal ◽  
Optimal Trajectory Planning

To solve the problem that the time-consuming optimization process of Genetic Algorithm (GA) can erode the expected time-saving brought by the algorithm, time-optimal trajectory planning based on cubic spline was used, after the modification to classical fitness sharing function of NGA, a dual-threaded method utilizing elite strategy characteristic was designed which was based on Niche Genetic Algorithm (NGA) with the fitness sharing technique. The simulation results show that the proposed method can mitigate the contradiction of the long term the optimization algorithm takes but a short running time the trajectory gets, demonstrating the effectiveness of the proposed method. Besides, the improved fitness sharing technique has reduced the subjective process of determining relevant parameters and the optimized trajectory results met performance constraints of the robot joints.

Optimal trajectory planning for robotic manipulators using improved teaching-learning-based optimization algorithm

2016 ◽  
Vol 43 (3) ◽  
pp. 308-316 ◽  
Author(s):  
Xueshan Gao ◽  
Yu Mu ◽  
Yongzhuo Gao
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Robotic Manipulators ◽  
Neighborhood Search ◽  
Local Optimum ◽  
Content Type ◽  
Time Optimal ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Optimal Trajectory Planning

Purpose The purpose of this paper is to propose a method of optimal trajectory planning for robotic manipulators that applies an improved teaching-learning-based optimization (ITLBO) algorithm. Design/methodology/approach The ITLBO algorithm possesses better ability to escape from the local optimum by integrating the original TLBO with variable neighborhood search. The trajectory of robotic manipulators complying with the kinematical constraints is constructed by fifth-order B-spline curves. The objective function to be minimized is execution time of the trajectory. Findings Experimental results with a 6-DOF robotic manipulator applied to surface polishing of metallic workpiece verify the effectiveness of the method. Originality/value The presented ITLBO algorithm is more efficient than the original TLBO algorithm and its variants. It can be applied to any robotic manipulators to generate time-optimal trajectories.

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