Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : March 06, 2023 - March 07, 2023
Most public infrastructure equipment in use today was built during a period of high economic growth and is rapidly aging. However, inspection workers have been decreasing and tools for inspecting buried infrastructure (e.g., handheld ground-penetrating radar) require a great amount of labor and time. Thus, autonomous mobile robots are required to improve efficiency and labor costs. High self-position estimation accuracy is required for autonomous movement and for specifying a position by comparing the coordinates of objects buried underground with information from a ground-penetrating radar. In this report, we describe a method using road surface motion images as a self-position estimation applicable to underground burial exploration robots. To compensate for accumulated errors, we propose an algorithm that records feature points at regular intervals. Experiments show that the error is corrected by using the accumulated feature points.
