RA-L 202026 citations

Time-Optimal Trajectory Planning for Flexible Joint Robots

Alessandro Palleschi, Riccardo Mengacci, Franco Angelini, Danilo Caporale, Lucia Pallottino, Alessandro De Luca, Manolo Garabini

Abstract

In this letter, a new approach is proposed to optimally plan the motion along a parametrized path for flexible joint robots, i.e., robots whose structure is purposefully provided with compliant elements. State-of-the-art methods efficiently solve the problem in case of torque-controlled rigid robots via a translation of the optimal control problem into a convex optimization problem. Recently, we showed that, for jerk-controlled rigid robots, the problem could be recast into a non-convex optimization problem. The non-convexity is given by bilinear constraints that can be efficiently handled through McCormick relaxations and spatial Branch-and-Bound techniques. In this letter, we show that, even in case of robots with flexible joints, the time-optimal trajectory planning problem can be recast into a non-convex problem in which the non-convexity is still given by bilinear constraints. We performed experimental tests on a planar 2R elastic manipulator to validate the benefits of the proposed approach. The scalability of the method for robots with multiple degrees of freedom is also discussed.

BibTeX
@inproceedings{ral2020_timeoptimaltraje,
  title = {Time-Optimal Trajectory Planning for Flexible Joint Robots},
  author = {Alessandro Palleschi and Riccardo Mengacci and Franco Angelini and Danilo Caporale and Lucia Pallottino and Alessandro De Luca and Manolo Garabini},
  booktitle = {RA-L 2020},
  year = {2020}
}
Time-Optimal Trajectory Planning for Flexible Joint Robots · RA-L 2020