start-ver=1.4
cd-journal=joma
no-vol=12
cd-vols=
no-issue=
article-no=
start-page=171824
end-page=171835
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2024
dt-pub=2024
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Passability-Based Local Planner Using Growing Neural Gas for an Autonomous Mobile Robot
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=3D spatial perception is one of the most important abilities for autonomous mobile robots. In environments with unknown objects, the ability to perform a local planner, which modifies the global path based on the perception results, is also required as an indispensable capability. In this paper, we propose a method based on Growing Neural Gas with Different Topologies (GNG-DT), which can be applied to unknown data, as a method for 3D spatial perception and local planner in unknown environments. First, we propose a method for extracting travelability perceptions from the features estimated by the topological structure of the GNG-DT. Next, we learn the topological structure of passability information based on the size of the robot from the extracted traversability percepts. Furthermore, we propose a local planner that uses the topological structure of traversability and passability learned from the point cloud currently perceived by the robot. In the experiments, we compared the cases where only traversability was used and where passability information was used in actual environments, and showed that the proposed method can plan a route that determines the area that the robot can actually pass through.
en-copyright=
kn-copyright=

en-aut-name=OzasaKoki
en-aut-sei=Ozasa
en-aut-mei=Koki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=TodaYuichiro
en-aut-sei=Toda
en-aut-mei=Yuichiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

en-aut-name=NakamuraYoshimasa
en-aut-sei=Nakamura
en-aut-mei=Yoshimasa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=

en-aut-name=MasudaToshiki
en-aut-sei=Masuda
en-aut-mei=Toshiki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=

en-aut-name=KonishiHirohide
en-aut-sei=Konishi
en-aut-mei=Hirohide
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=

en-aut-name=MatsunoTakayuki
en-aut-sei=Matsuno
en-aut-mei=Takayuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=

affil-num=1
en-affil=Graduate School of Environmental, Life, Natural Science and Technology, Okayama University
kn-affil=

affil-num=2
en-affil=Graduate School of Environmental, Life, Natural Science and Technology, Okayama University
kn-affil=

affil-num=3
en-affil=Tokyo Metropolitan Industrial Technology Research Institute
kn-affil=

affil-num=4
en-affil=Tokyo Metropolitan Industrial Technology Research Institute
kn-affil=

affil-num=5
en-affil=NSK Ltd.
kn-affil=

affil-num=6
en-affil=Graduate School of Environmental, Life, Natural Science and Technology, Okayama University
kn-affil=
en-keyword=Autonomous mobile robot
kn-keyword=Autonomous mobile robot
en-keyword=growing neural gas
kn-keyword=growing neural gas
en-keyword=local planner
kn-keyword=local planner
END