Teach-and-Replay of Mobile Robot with Particle Filter on Episode
Ryuichi Ueda, Masahiro Kato, Atsushi Saito, Ryo Okazaki
Abstract
A novel method for replaying behavior of a mobile robot from its memory of past experiences is presented in this paper. The method is a version of a particle filter on episode (PFoE), which applies a particle filter on the memory so as to efficiently find some similar situations with the current one. Though the original PFoE was proposed as a reinforcement learning method, we once removed the reward system from the original one so as to apply it to task teaching. In the experiment, we gave several kinds of motion to a micromouse type robot with the proposed method through a gamepad. The robot replayed the behaviors robustly with sensor feedback after several number of repetitive teaching.
BibTeX
@inproceedings{icra2018_teachandreplayof,
title = {Teach-and-Replay of Mobile Robot with Particle Filter on Episode},
author = {Ryuichi Ueda and Masahiro Kato and Atsushi Saito and Ryo Okazaki},
booktitle = {ICRA 2018},
year = {2018}
}