Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162467
Full metadata record
DC FieldValueLanguage
dc.contributor.authorDong, Huixuen_US
dc.contributor.authorWeng, Ching-Yenen_US
dc.contributor.authorGuo, Chuangqiangen_US
dc.contributor.authorYu, Haoyongen_US
dc.contributor.authorChen, I-Mingen_US
dc.date.accessioned2022-10-21T05:00:02Z-
dc.date.available2022-10-21T05:00:02Z-
dc.date.issued2021-
dc.identifier.citationDong, H., Weng, C., Guo, C., Yu, H. & Chen, I. (2021). Real-time avoidance strategy of dynamic obstacles via half model-free detection and tracking with 2D lidar for mobile robots. IEEE/ASME Transactions On Mechatronics, 26(4), 2215-2225. https://dx.doi.org/10.1109/TMECH.2020.3034982en_US
dc.identifier.issn1083-4435en_US
dc.identifier.urihttps://hdl.handle.net/10356/162467-
dc.description.abstractAvoidance is a necessary capability for a mobile robot to perform tasks, such as delivering objects in household or industrial scenarios. The existing avoidance strategy based on timed elastic band local planner and cost-map provided by robotics operating system cannot realize the excellent performance when a robot and an obstacle both move. In this article, we present a real-time, simple, and reliable approach to detecting and tracking obstacles via a two-dimensional lidar in dynamic scenarios where the mobile robot and the obstacle are moving. Obstacles are represented by a set of points against their outlines and the information of obstacles is initialized and updated via the raw laser measurement. First, the obstacle is detected by three main steps: preprocessing, segmentation, and merging, classification of consequent measurements. Second, we use a hierarchical method to realize data associations for figuring out the corresponding matches among obstacles with the consecutive time. Last, after doing the data association, we need to estimate the motion of the dynamic obstacle for being tracked by the Kalman filter. Extensive experiments performed in the simulation and practical scenarios indicate that the proposed method enables a mobile robot to perform dynamic avoidances efficiently [Real-time Avoidance Strategy of Dynamic Obstacles via Half Model-free Detection and Tracking (T-MECH)].en_US
dc.language.isoenen_US
dc.relation.ispartofIEEE/ASME Transactions on Mechatronicsen_US
dc.rights© 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. All rights reserved.en_US
dc.subjectEngineering::Mechanical engineering::Robotsen_US
dc.titleReal-time avoidance strategy of dynamic obstacles via half model-free detection and tracking with 2D lidar for mobile robotsen_US
dc.typeJournal Articleen
dc.contributor.researchRobotics Research Centreen_US
dc.identifier.doi10.1109/TMECH.2020.3034982-
dc.identifier.scopus2-s2.0-85096114924-
dc.identifier.issue4en_US
dc.identifier.volume26en_US
dc.identifier.spage2215en_US
dc.identifier.epage2225en_US
dc.subject.keywordsTwo Dimensional Displaysen_US
dc.subject.keywordsLaser Radaren_US
dc.description.acknowledgementThis work was supported by the State Key Laboratory of Robotics and System (HIT) Open Cooperation under Grant SKLRS-2019-KF-02. (Corresponding author: Chuangqiang Guo.)en_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
Appears in Collections:RRC Journal Articles

SCOPUSTM   
Citations 50

7
Updated on Jan 31, 2023

Web of ScienceTM
Citations 20

11
Updated on Jan 26, 2023

Page view(s)

36
Updated on Feb 4, 2023

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.