—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
Abstract— Trajectory planning and optimization is a fundamental problem in articulated robotics. It is often viewed as a two phase problem of initial feasible path planning aroun...
Abstract— We present the Constrained Bi-directional RapidlyExploring Random Tree (CBiRRT) algorithm for planning paths in configuration spaces with multiple constraints. This al...
Dmitry Berenson, Siddhartha S. Srinivasa, Dave Fer...
— Robots acting in populated environments must be capable of safe but also time efficient navigation. Trying to completely avoid regions resulting from worst case predictions of...
Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...