Pei Yingjian, Eiji Hayashi, Sakmongkon Chumkamon
MIST, Hayashi Lab, Kyushu Institute of Technology, 680-4 Kawazu. Iizuka-shi, Fukuoka 820-8502, Japan
pp. 22–26
ABSTRACT
This research is part of the Yaskawa Motoman Robot Autonomous Control Project, which aims to map the real workspace in a virtual environment using a depth camera mounted on the robot, and to plan the robot's autonomous obstacle avoidance path based on the 3D octomap. The main tool used in this study is RTAB-Map, which is based on the built-in handheld mapping scheme to improve it to meet our actual needs. After the actual test, our solution shows finer mapping accuracy, can update the map data in real time, and the perception of obstacles within the field of view is more comprehensive, but there is still a lot of room for optimizing the mapping speed.

ARTICLE INFO
Article History
Received 25 November 2020
Accepted 11 May 2021

Keywords
3D SLAM
Semantic segmentation
Point cloud
ROS

JAALR2105

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