Finite distribution estimation-based dynamic window approach to a reliable obstacle-avoidance of mobile robots

Simple item page
dc.contributor.authorLee, D.H.
dc.contributor.authorLee, S.S.
dc.contributor.authorAhn, C.K.
dc.contributor.authorShi, P.
dc.contributor.authorLim, C.C.
dc.date.issued2021
dc.description.abstractThis paper proposes a novel obstacle avoidance algorithm for a mobile robot based on finite memory filtering (FMF) in unknown dynamic environments. To overcome the limitations of the existing dynamic window approach (DWA), we propose a new version of the DWA, called the finite distribution estimation-based dynamic window approach (FDEDWA), which is an algorithm that avoids dynamic obstacles through estimating the overall distribution of obstacles. FDEDWA estimates the distribution of obstacles through the FMF and predicts the future distribution of obstacles. The FMF is derived to minimize the effect of the measurement noise through the Frobenius norm and covariance matrix adaptation evolution strategy (CMA-ES). The estimated information is used to derive the control input for the robust mobile robot navigation effectively. FDEDWA allows for the fast perception of the dynamic environment and superior estimation performance, and the mobile robot can be controlled by a more optimal path while maintaining real-time performance. To demonstrate the performance of the proposed algorithm, simulations and experiments were carried out under dynamic environments by comparing the latest dynamic window for dynamic obstacle (DW4DO) and the existing DWA.
dc.description.statementofresponsibilityDhong Hun Lee, Sang Su Lee, Choon Ki Ahn, Peng Shi, Cheng-Chew Lim
dc.identifier.citationIEEE Transactions on Industrial Electronics, 2021; 68(10):9998-10006
dc.identifier.doi10.1109/TIE.2020.3020024
dc.identifier.issn0278-0046
dc.identifier.issn1557-9948
dc.identifier.orcidShi, P. [0000-0001-6295-0405] [0000-0001-8218-586X] [0000-0002-0864-552X] [0000-0002-1358-2367] [0000-0002-5312-5435]
dc.identifier.orcidLim, C.C. [0000-0002-2463-9760]
dc.identifier.urihttps://hdl.handle.net/2440/132565
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.relation.granthttp://purl.org/au-research/grants/arc/DP170102644
dc.rights© 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
dc.source.urihttps://doi.org/10.1109/tie.2020.3020024
dc.subjectCovariance matrix adaptation evolution Strategy; dynamic window approach; finite memory filter; obstacle avoidance
dc.titleFinite distribution estimation-based dynamic window approach to a reliable obstacle-avoidance of mobile robots
dc.typeJournal article
pubs.publication-statusPublished

Files

Collections

Electrical and Electronic Engineering publications