Time-Optimal Trajectory Planning for Flexible Joint Robots

Home / Publications / 2020 / Time-Optimal Trajectory Planning for Flexible Joint Robots

Alessandro Palleschi, Riccardo Mengacci, Franco Angelini, Danilo Caporale,
Lucia Pallottino, Alessandro De Luca, and Manolo Garabini
Time-Optimal Trajectory Planning for Flexible Joint Robots
IEEE Robotics and Automation Letters, Vol. 5, No. 2, April 2020

 

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.

 

@article {3885,
title = {Time-Optional Trajectory Planning for Flexible Joint Robots},
journal = {IEEE Robotics and Automation Letters},
volume = {5},
year = {2020},
month = {01/2020},
chapter = {938},
doi= {https://doi.org/10.1109/LRA.2020.2965861},
url = {https://ieeexplore.ieee.org/document/8957077/authors$\#$authors},
author = {A. Palleschi and R. Mengacci and F. Angelini and D. Caporale and L. Pallottino and A. De Luca and M. Garabini
}