—We formulate and address the problem of planning a pushing manipulation by a mobile robot which tries to rearrange several movable objects in its work space. We present an algor...
— This paper presents a new redundancy resolution approach based on the gradient projection method, which allows to avoid man-machine and machine-machine collisions as well as si...
Yuta Komoguchi, Ken'ichi Yano, Angelika Peer, Mart...
Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
Jun Morimoto, Christopher G. Atkeson, Gen Endo, Go...
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...
— We introduce a method for constructing provably safe smooth feedback laws for car-like robots in obstaclecluttered polygonal environments. The robot is taken to be a point with...