@inproceedings{42d74b4d2e994881b533213e54415e3e,
title = "Keyframe Tracking-based Path Planner for Vision-based Autonomous Mobile Robots",
abstract = "Recently, visual navigation systems have been actively studied in mobile robot navigation. Such systems create keyframes to correct and track the pose of a mobile robot. However, unlike manual control, the mobile robot under autonomous control is likely to fail to follow the keyframe path accurately due to control errors. To deal with this problem, we propose a novel local path planner called a keyframe tracking-based path planner (KTPP) that helps a robot to track the keyframe path continuously. The KTPP constantly monitors whether or not the robot is on the keyframe path and if not, a local path is generated to guide a robot to return to the desired keyframe path. Various experiments show that the KTPP lead the robot to arrive at the goal point more accurately.",
keywords = "keyframes, Path planning, PnP, visual SLAM",
author = "Choi, {Ji Hoon} and Chae, {Hee Won} and Song, {Jae Bok}",
year = "2019",
month = oct,
doi = "10.23919/ICCAS47443.2019.8971460",
language = "English",
series = "International Conference on Control, Automation and Systems",
publisher = "IEEE Computer Society",
pages = "1054--1057",
booktitle = "ICCAS 2019 - 2019 19th International Conference on Control, Automation and Systems, Proceedings",
note = "19th International Conference on Control, Automation and Systems, ICCAS 2019 ; Conference date: 15-10-2019 Through 18-10-2019",
}