Global Path and Local Motion Planning for Humanoid Climbing Robot Using Kinect Sensor

Dung Anh Nguyen, Akira Shimada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a study on improving the adaptability of humanoid climbing robots in vertical environments. Although the robot is intended to be used for rescue and load-bearing in mountains or other hazardous areas in the future, this paper focuses on a path planning and local planning algorithm for humanoid robot wall climbing as the initial phase of our development. The first step is to acquire a depth map to extract accurate climbing holds on the vertical wall. Secondly, we propose a global planning algorithm for the humanoid robot using data from Kinect. During climbing, the humanoid robot utilizes the local planning algorithm, based on quasi-static equilibrium, to adjust its body posture to remain in an equilibrium state. Finally, all algorithms are evaluated with a simple, practical example for a humanoid climbing robot system, and its effectiveness is demonstrated experimentally in a real environment.

Original languageEnglish
Title of host publicationAdvances in Asian Mechanism and Machine Science - Proceedings of IFToMM Asian MMS 2021
EditorsNguyen Van Khang, Nguyen Quang Hoang, Marco Ceccarelli
PublisherSpringer Science and Business Media B.V.
Pages109-122
Number of pages14
ISBN (Print)9783030918910
DOIs
Publication statusPublished - 2022
Event6th IFToMM Asian Mechanisms and Machine Science Conference, Asian MMS 2021 - Virtual, Online
Duration: 2021 Dec 152021 Dec 18

Publication series

NameMechanisms and Machine Science
Volume113 MMS
ISSN (Print)2211-0984
ISSN (Electronic)2211-0992

Conference

Conference6th IFToMM Asian Mechanisms and Machine Science Conference, Asian MMS 2021
CityVirtual, Online
Period21/12/1521/12/18

Keywords

  • Climbing
  • Humanoid robot
  • Kinect
  • Motion planning

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering

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