Host: The Japanese Society for Artificial Intelligence
Name : The 33rd Annual Conference of the Japanese Society for Artificial Intelligence, 2019
Number : 33
Location : [in Japanese]
Date : June 04, 2019 - June 07, 2019
This paper presents a new approach named physics projection, through which robots can learn the physical world and predict the effects of their actions actively and online. Physics projection consists of three components: a robot, physical world model, and physics engine. The process of physics projection has a double loop structure comprising (1) a learning loop of the physical world model and (2) a simulation search loop. Experiments were performed using the TurtleBot3 mobile robot and Unity graphic engine. The results clearly showed that the robot predicted the effects of its various actions under the given physical conditions and successfully executed the tasks of carrying a wine glass without dropping it and a cup filled with water without spilling. The robot could predict a catastrophic effect that could not be predicted by a human operator.
