MPC-based humanoid pursuit-evasion in the presence of obstacles
Daniele De Simone, Nicola Scianca, Paolo Ferrari, Leonardo Lanari, Giuseppe Oriolo
Abstract
We consider a pursuit-evasion problem between humanoids in the presence of obstacles. In our scenario, the pursuer enters the safety area of the evader headed for collision, while the latter executes a fast evasive motion. Control schemes are designed for both the pursuer and the evader. They are structurally identical, although the objectives are different: the pursuer tries to align its direction of motion with the line-of-sight to the evader, whereas the evader tries to move in a direction orthogonal to the line-of-sight to the pursuer. At the core of the control architecture is a Model Predictive Control scheme for generating a stable gait. This allows for the inclusion of workspace obstacles, which we take into account at two levels: during the determination of the footsteps orientation and as an explicit MPC constraint. We illustrate the results with simulations on NAO humanoids.
BibTeX
@inproceedings{iros2017_mpcbasedhumanoid,
title = {MPC-based humanoid pursuit-evasion in the presence of obstacles},
author = {Daniele De Simone and Nicola Scianca and Paolo Ferrari and Leonardo Lanari and Giuseppe Oriolo},
booktitle = {IROS 2017},
year = {2017}
}