Keyframe Tracking-based Path Planner for Vision-based Autonomous Mobile Robots

Ji Hoon Choi; Hee Won Chae; Jae Bok Song

doi:10.23919/ICCAS47443.2019.8971460

Keyframe Tracking-based Path Planner for Vision-based Autonomous Mobile Robots

Ji Hoon Choi
, Hee Won Chae
, Jae Bok Song

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

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.

Original language	English
Title of host publication	ICCAS 2019 - 2019 19th International Conference on Control, Automation and Systems, Proceedings
Publisher	IEEE Computer Society
Pages	1054-1057
Number of pages	4
ISBN (Electronic)	9788993215182
DOIs	https://doi.org/10.23919/ICCAS47443.2019.8971460
Publication status	Published - 2019 Oct
Event	19th International Conference on Control, Automation and Systems, ICCAS 2019 - Jeju, Korea, Republic of Duration: 2019 Oct 15 → 2019 Oct 18

Publication series

Name	International Conference on Control, Automation and Systems
Volume	2019-October
ISSN (Print)	1598-7833

Conference

Conference	19th International Conference on Control, Automation and Systems, ICCAS 2019
Country/Territory	Korea, Republic of
City	Jeju
Period	19/10/15 → 19/10/18

Bibliographical note

Funding Information:
This work was supported by IITP grant funded by the Korea Government MSIT. (o. 20N 18-0-00622).

Publisher Copyright:
© 2019 Institute of Control, Robotics and Systems - ICROS.

Keywords

Path planning
PnP
keyframes
visual SLAM

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.23919/ICCAS47443.2019.8971460

Cite this

Choi, J. H., Chae, H. W., & Song, J. B. (2019). Keyframe Tracking-based Path Planner for Vision-based Autonomous Mobile Robots. In ICCAS 2019 - 2019 19th International Conference on Control, Automation and Systems, Proceedings (pp. 1054-1057). Article 8971460 (International Conference on Control, Automation and Systems; Vol. 2019-October). IEEE Computer Society. https://doi.org/10.23919/ICCAS47443.2019.8971460

Keyframe Tracking-based Path Planner for Vision-based Autonomous Mobile Robots. / Choi, Ji Hoon; Chae, Hee Won; Song, Jae Bok.
ICCAS 2019 - 2019 19th International Conference on Control, Automation and Systems, Proceedings. IEEE Computer Society, 2019. p. 1054-1057 8971460 (International Conference on Control, Automation and Systems; Vol. 2019-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Choi, JH, Chae, HW & Song, JB 2019, Keyframe Tracking-based Path Planner for Vision-based Autonomous Mobile Robots. in ICCAS 2019 - 2019 19th International Conference on Control, Automation and Systems, Proceedings., 8971460, International Conference on Control, Automation and Systems, vol. 2019-October, IEEE Computer Society, pp. 1054-1057, 19th International Conference on Control, Automation and Systems, ICCAS 2019, Jeju, Korea, Republic of, 19/10/15. https://doi.org/10.23919/ICCAS47443.2019.8971460

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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 = "Path planning, PnP, keyframes, visual SLAM",

author = "Choi, \{Ji Hoon\} and Chae, \{Hee Won\} and Song, \{Jae Bok\}",

note = "Funding Information: This work was supported by IITP grant funded by the Korea Government MSIT. (o. 20N 18-0-00622). Publisher Copyright: {\textcopyright} 2019 Institute of Control, Robotics and Systems - ICROS.; 19th International Conference on Control, Automation and Systems, ICCAS 2019 ; Conference date: 15-10-2019 Through 18-10-2019",

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N2 - 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.

AB - 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.

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Keyframe Tracking-based Path Planner for Vision-based Autonomous Mobile Robots

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this