Time-optimal path tracking for articulated robot along spline curves based on master-slave strategy

2016 ◽  
Author(s):  
Xiaojing Yu ◽  
Xiaoqi Tang ◽  
Bosheng Ye ◽  
Bao Song ◽  
Xiangdong Zhou
Keyword(s):  
Optimal Path ◽  
Path Tracking ◽  
Spline Curves ◽  
Time Optimal ◽  
Articulated Robot

Smooth Time-Optimal Path Tracking for Robot Manipulators With Kinematic Constraints

2020 ◽  
Author(s):  
Kui Hu ◽  
Yunfei Dong ◽  
Dan Wu
Keyword(s):  
Robot Manipulators ◽  
Optimal Path ◽  
Path Tracking ◽  
Control Input ◽  
Kinematic Constraints ◽  
Computation Efficiency ◽  
Planning Approach ◽  
Time Optimal ◽  
Difference Of Convex ◽  
The Difference

Abstract Previous works solve the time-optimal path tracking problems considering piece-wise constant parametrization for the control input, which may lead to the discontinuous control trajectory. In this paper, a practical smooth minimum time trajectory planning approach for robot manipulators is proposed, which considers complete kinematic constraints including velocity, acceleration and jerk limits. The main contribution of this paper is that the control input is represented as the square root of a polynomial function, which reformulates the velocity and acceleration constraints into linear form and transforms the jerk constraints into the difference of convex form so that the time-optimal problem can be solved through sequential convex programming (SCP). The numerical results of a real 7-DoF manipulator show that the proposed approach can obtain very smooth velocity, acceleration and jerk trajectories with high computation efficiency.

scholarly journals Near Time-Optimal Path Tracking Method for Waiter Motion Problem

2017 ◽  
Vol 50 (1) ◽  
pp. 4929-4934 ◽  
Author(s):  
Gábor Csorvási ◽  
Ákos Nagy ◽  
István Vajk
Keyword(s):  
Optimal Path ◽  
Path Tracking ◽  
Tracking Method ◽  
Time Optimal ◽  
Motion Problem ◽  
Path Tracking Method

Time-Optimal Path Tracking for Jerk Controlled Robots

2019 ◽  
Vol 4 (4) ◽  
pp. 3932-3939 ◽  
Author(s):  
Alessandro Palleschi ◽  
Manolo Garabini ◽  
Danilo Caporale ◽  
Lucia Pallottino
Keyword(s):  
Optimal Path ◽  
Path Tracking ◽  
Time Optimal

Time-optimal path tracking for robots a numerical integration-like approach combined with an iterative learning algorithm

2019 ◽  
Vol 46 (6) ◽  
pp. 763-778
Author(s):  
Lin Li ◽  
Jiadong Xiao ◽  
Yanbiao Zou ◽  
Tie Zhang
Keyword(s):  
Numerical Integration ◽  
Dynamic Model ◽  
Learning Algorithm ◽  
Optimal Path ◽  
Tracking Error ◽  
Path Tracking ◽  
Iterative Learning ◽  
Content Type ◽  
Accelerated Motion ◽  
Time Optimal

Purpose The purpose of this paper is to propose a precise time-optimal path tracking approach for robots under kinematic and dynamic constraints to improve the work efficiency of robots and guarantee tracking accuracy. Design/methodology/approach In the proposed approach, the robot path is expressed by a scalar path coordinate and discretized into N points. The motion between two neighbouring points is assumed to be uniformly accelerated motion, so the time-optimal trajectory that satisfies constraints is obtained by using equations of uniformly accelerated motion instead of numerical integration. To improve dynamic model accuracy, the Coulomb and viscous friction are taken into account (while most publications neglect these effects). Furthermore, an iterative learning algorithm is designed to correct model-plant mismatch by adding an iterative compensation item into the dynamic model at each discrete point before trajectory planning. Findings An experiment shows that compared with the sequential convex log barrier method, the proposed numerical integration-like (NI-like) approach has less computation time and a smoother planning trajectory. Compared with the experimental results before iteration, the torque deviation, tracking error and trajectory execution time are reduced after 10 iterations. Originality/value As the proposed approach not only yields a time-optimal solution but also improves tracking performance, this approach can be used for any repetitive robot tasks that require more rapidity and less tracking error, such as assembly.

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