scholarly journals Time Optimal Path Tracking for Industrial Robots with Low Cost Computational Unit using Model Predictive Control

PAMM ◽  
2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Matthias Jörgl ◽  
Hubert Gattringer ◽  
Andreas Müller
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Low Cost ◽  
Optimal Path ◽  
Path Tracking ◽  
Industrial Robots ◽  
Time Optimal

scholarly journals Successive dynamic programming and subsequent spline optimization for smooth time optimal robot path tracking

2015 ◽  
Vol 6 (2) ◽  
pp. 245-254 ◽  
Author(s):  
M. Oberherber ◽  
H. Gattringer ◽  
A. Müller
Keyword(s):  
Industrial Robot ◽  
Optimal Path ◽  
Industrial Applications ◽  
Path Tracking ◽  
Industrial Robots ◽  
Dynamic Constraints ◽  
Individual Segment ◽  
Numerical Effort ◽  
Time Optimal ◽  
Robot Path

Abstract. The time optimal path tracking for industrial robots regards the problem of generating trajectories that follow predefined end-effector (EE) paths in shortest time possible taking into account kinematic and dynamic constraints. The complicated tasks used in industrial applications lead to very long EE paths. At the same time smooth trajectories are mandatory in order to increase the service life. The consideration of jerk and torque rate restrictions, necessary to achieve smooth trajectories, causes enormous numerical effort, and increases computation times. This is in particular due to the high number of optimization variables required for long geometric paths. In this paper we propose an approach where the path is split into segments. For each individual segment a smooth time optimal trajectory is determined and represented by a spline. The overall trajectory is then found by assembling these splines to the solution for the whole path. Further we will show that by using splines, the jerks are automatically bounded so that the jerk constraints do not have to be imposed in the optimization, which reduces the computational complexity. We present experimental results for a six-axis industrial robot. The proposed approach provides smooth time optimal trajectories for arbitrary long geometric paths in an efficient way.

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.

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