Robust Human Tracking of a Crawler Robot
Author(s) -
Yasuaki Orita,
Takanori Fukao
Publication year - 2019
Publication title -
journal of robotics and mechatronics
Language(s) - English
Resource type - Journals
eISSN - 1883-8049
pISSN - 0915-3942
DOI - 10.20965/jrm.2019.p0194
Subject(s) - web crawler , robot , search and rescue , computer science , robustness (evolution) , rescue robot , artificial intelligence , mobile robot , real time computing , computer vision , simulation , biochemistry , chemistry , world wide web , gene
Carrying out firefighting activities at disaster sites is extremely difficult. Therefore, robots that support and enhance these operations are required. In this paper, a crawler robot that tracks the moving path of a firefighter is proposed. It is commonly believed that trained firefighters select the best route; thus, it was assumed that this route is the easiest for the crawler robot as well. Using two 3D light detection and ranging sensors, once the firefighter’s coordinates are detected, the coordinates are combined with 3D simultaneous localization and mapping results, then a target path is generated. The crawler robot follows the path using inverse optimal tracking control. The controller has a stability margin that guarantees robustness, which is an ideal property for disaster response robots used in severe conditions. The results of several experiments show that the proposed system is effective and practical for the crawler robot.
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