Growing Neural Gasを用いた半自律遠隔操作システムの操作評価

抄録

This paper focusses on a semi-autonomous teleoperation system for reducing heavy burden of an operator. Our proposed path planning system is based on Growing Neural Gas (GNG) for learning a topological structure from a metric map built by SLAM for applying the path planning to an unknown environment. At first, this paper explains our proposed semi-autonomous teleoperation system using a touch interface and learning algorithm of the topological map. Next, this paper explains the path planning that utilizes the topological map built by GNG. Finally, for verifying the effectiveness of our proposed teleoperation system, this paper conducted on experimental results to compare the beginner and expert operators.