@inproceedings{d39b811c86094b58beff522ba1bcfe16,
title = "A Collision-Free Pedestrian-Following System for Mobile Robots Base on Path Planning",
abstract = "In order to overcome the problems of collision avoidance and the pedestrian target loss in pedestrian-following system. This paper proposes a Collision-Free pedestrian following approach with a multi-sensor fusion-based pedestrian detector module and a path planning module. The pedestrian detector module use extended Kalman filter(EKF) to fuse a camera and a 3D LiDAR data for the target pedestrian positioning and perceive obstacles.for the path planning module, In order to track pedestrians in real time and collision-free, a global path planner and a local path planner will work simultaneously. Overall, we conducted experiments on pedestrian following in different environmental conditions to evaluate the performance of ours proposed approach.",
keywords = "Collision Avoidance, extended Kalman filter, mobile robot, pedestrian following, person detector, sensor fusion",
author = "Hong Zhang and Songyan Wang and Ju Huo and Tao Chao",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 20th IEEE International Conference on Mechatronics and Automation, ICMA 2023 ; Conference date: 06-08-2023 Through 09-08-2023",
year = "2023",
doi = "10.1109/ICMA57826.2023.10215802",
language = "英语",
series = "2023 IEEE International Conference on Mechatronics and Automation, ICMA 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1853--1858",
booktitle = "2023 IEEE International Conference on Mechatronics and Automation, ICMA 2023",
address = "美国",
}