A model for optimising the size of climbing robots for navigating truss structures

Wesley Au, Tomoki Sakaue, Dikai Liu

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

Abstract

Truss structures can be found in many buildings and civil infrastructure such as bridges and towers. But as these architectures age, their maintenance is required to keep them structurally sound. A legged robotic solution capable of climbing these structures for maintenance is sought, but determining the size and shape of such a robot to maximise structure coverage is a challenging task. This paper proposes a model in which the size of a multi-legged robot is optimised for coverage in a truss structure. A detailed representation of a truss structure is presented, which forms the novel framework for constraint modelling. With this framework, the overall truss structure coverage is modelled, given a robot's size and its climbing performance constraints. This is set up as an optimisation problem, such that its solution represents the optimum size of the robot that satisfies all constraints. Three case studies of practical climbing applications are conducted to verify the model. By intuitive analysis of the model's output data, the results show that the model accurately applies these constraints in a variety of truss structures.

Original languageEnglish
Title of host publication2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages3754-3760
Number of pages7
ISBN (Electronic)9781728162126
DOIs
Publication statusPublished - 2020
Externally publishedYes
EventIEEE/RSJ International Conference on Intelligent Robots and Systems 2020 - Virtual, Las Vegas, United States of America
Duration: 24 Jan 202124 Jan 2021
https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/9340668/proceeding
https://www.iros2020.org (Website)

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
PublisherIEEE, Institute of Electrical and Electronics Engineers
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

ConferenceIEEE/RSJ International Conference on Intelligent Robots and Systems 2020
Abbreviated titleIROS 2020
CountryUnited States of America
CityLas Vegas
Period24/01/2124/01/21
Internet address

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