— Computationally efficient motion planning must avoid exhaustive exploration of configuration space. We argue that this can be accomplished most effectively by carefully balan...
The paper describes our first experiments on Reinforcement Learning to steer a real robot car. The applied method, Neural Fitted Q Iteration (NFQ) is purely data-driven based on ...
Martin Riedmiller, Michael Montemerlo, Hendrik Dah...
— Randomly expanding trees are very effective in exploring high-dimensional spaces. Consequently, they are a powerful algorithmic approach to sampling-based single-query motion p...
This paper is concerned with the problem of intrinsically assigning meaning to the signals responsible for autonomic responses in a system. Without an associated cognitive system,...
Martin Randles, A. Taleb-Bendiab, Philip Miseldine
Real-world objects exhibit rich physical interaction behaviours on contact. Such behaviours depend on how heavy and hard it is when held, how its surface feels when touched, how i...
Hiromi T. Tanaka, Kiyotaka Kushihama, Naoki Ueda, ...