Home // International Journal On Advances in Systems and Measurements, volume 16, numbers 1 and 2, 2023 // View article
Authors:
Ibuki Yoshida
Akihiko Yoshida
Masafumi Hashimoto
Kazuhiko Takahashi
Keywords: helmet LiDAR/IMU; micromobility; environmental map building; moving object tracking; road boundary detection; road unevenness detection; road surface condition estimation.
Abstract:
This paper presents a method of environmental map building and moving object tracking using Light Detection And Ranging (LiDAR) and Inertial Measurement Unit (IMU) mounted on a smart helmet worn by a micromobility rider. This presented method can be used for active safety for micromobility, such as bicycles, e-bikes, and electric scooters. Distortion in scan data from LiDAR is corrected by estimating the helmet pose (three-dimensional (3D) position and attitude angle) based on information obtained from normal distributions transform scan matching and IMU. The corrected LiDAR scan data are classified into scan data on road surfaces, road boundaries, stationary objects, and moving objects in the environments. Moving object scan data are used for moving object tracking. Stationary object and road boundary scan data are used to represent 3D stationary objects and road obstacles, such as curbs, gutters, and steps. Road surface scan data from LiDAR are in conjunction with IMU acceleration, and small road unevenness, such as potholes and humps, is detected to reduce the falling risk of micromobility. Furthermore, road surface conditions are identified by integrating IMU acceleration data, and a road surface condition map is constructed to provide safety and comfortability for micromobility riders in environments. Experiments conducted on a road on our university campus demonstrate the effectiveness of the proposed method.
Pages: 40 to 52
Copyright: Copyright (c) to authors, 2023. Used with permission.
Publication date: June 30, 2023
Published in: journal
ISSN: 1942-261x