Name
Abstract | ||
|---|---|---|
Recent advances in planning and control of robot manipulators make an increasing use of optimization-based techniques, such as model predictive control. In this framework, ensuring the feasibility of the online optimal control problem is a key issue. In the case of manipulators with bounded joint positions, velocities, and accelerations, feasibility can be guaranteed by limiting the set of admissible velocities and positions to a viable set. However, this results in the imposition of nonlinear optimization constraints. In this paper, we analyze the feasibility of the optimal control problem and we propose a method to construct a viable convex polyhedral that ensures feasibility of the optimal control problem by means of a given number of linear constraints. Experimental and numerical results on an industrial manipulator show the validity of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/robotics7030041 | ROBOTICS |
Keywords | Field | DocType |
manipulators,trajectory planning,kinematic constraints,optimization,viability,inverse kinematics | Kinematics,Optimal control,Inverse kinematics,Control theory,Nonlinear programming,Model predictive control,Regular polygon,Control engineering,Engineering,Limiting,Bounded function | Journal |
Volume | Issue | ISSN |
7 | 3.0 | 2218-6581 |
Citations | PageRank | References |
1 | 0.37 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marco Faroni | 1 | 3 | 1.78 |
| Manuel Beschi | 2 | 25 | 10.40 |
| Nicola Pedrocchi | 3 | 52 | 13.22 |
| Antonio Visioli | 4 | 224 | 40.89 |