Cargando…
Traversability analysis with vision and terrain probing for safe legged robot navigation
Inspired by human behavior when traveling over unknown terrain, this study proposes the use of probing strategies and integrates them into a traversability analysis framework to address safe navigation on unknown rough terrain. Our framework integrates collapsibility information into our existing tr...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441904/ https://www.ncbi.nlm.nih.gov/pubmed/36071857 http://dx.doi.org/10.3389/frobt.2022.887910 |
_version_ | 1784782692590551040 |
---|---|
author | Haddeler, Garen Chuah, Meng Yee (Michael) You, Yangwei Chan, Jianle Adiwahono, Albertus H. Yau, Wei Yun Chew, Chee-Meng |
author_facet | Haddeler, Garen Chuah, Meng Yee (Michael) You, Yangwei Chan, Jianle Adiwahono, Albertus H. Yau, Wei Yun Chew, Chee-Meng |
author_sort | Haddeler, Garen |
collection | PubMed |
description | Inspired by human behavior when traveling over unknown terrain, this study proposes the use of probing strategies and integrates them into a traversability analysis framework to address safe navigation on unknown rough terrain. Our framework integrates collapsibility information into our existing traversability analysis, as vision and geometric information alone could be misled by unpredictable non-rigid terrains such as soft soil, bush area, or water puddles. With the new traversability analysis framework, our robot has a more comprehensive assessment of unpredictable terrain, which is critical for its safety in outdoor environments. The pipeline first identifies the terrain’s geometric and semantic properties using an RGB-D camera and desired probing locations on questionable terrains. These regions are probed using a force sensor to determine the risk of terrain collapsing when the robot steps over it. This risk is formulated as a collapsibility metric, which estimates an unpredictable region’s ground collapsibility. Thereafter, the collapsibility metric, together with geometric and semantic spatial data, is combined and analyzed to produce global and local traversability grid maps. These traversability grid maps tell the robot whether it is safe to step over different regions of the map. The grid maps are then utilized to generate optimal paths for the robot to safely navigate to its goal. Our approach has been successfully verified on a quadrupedal robot in both simulation and real-world experiments. |
format | Online Article Text |
id | pubmed-9441904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94419042022-09-06 Traversability analysis with vision and terrain probing for safe legged robot navigation Haddeler, Garen Chuah, Meng Yee (Michael) You, Yangwei Chan, Jianle Adiwahono, Albertus H. Yau, Wei Yun Chew, Chee-Meng Front Robot AI Robotics and AI Inspired by human behavior when traveling over unknown terrain, this study proposes the use of probing strategies and integrates them into a traversability analysis framework to address safe navigation on unknown rough terrain. Our framework integrates collapsibility information into our existing traversability analysis, as vision and geometric information alone could be misled by unpredictable non-rigid terrains such as soft soil, bush area, or water puddles. With the new traversability analysis framework, our robot has a more comprehensive assessment of unpredictable terrain, which is critical for its safety in outdoor environments. The pipeline first identifies the terrain’s geometric and semantic properties using an RGB-D camera and desired probing locations on questionable terrains. These regions are probed using a force sensor to determine the risk of terrain collapsing when the robot steps over it. This risk is formulated as a collapsibility metric, which estimates an unpredictable region’s ground collapsibility. Thereafter, the collapsibility metric, together with geometric and semantic spatial data, is combined and analyzed to produce global and local traversability grid maps. These traversability grid maps tell the robot whether it is safe to step over different regions of the map. The grid maps are then utilized to generate optimal paths for the robot to safely navigate to its goal. Our approach has been successfully verified on a quadrupedal robot in both simulation and real-world experiments. Frontiers Media S.A. 2022-08-22 /pmc/articles/PMC9441904/ /pubmed/36071857 http://dx.doi.org/10.3389/frobt.2022.887910 Text en Copyright © 2022 Haddeler, Chuah, You, Chan, Adiwahono, Yau and Chew. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Robotics and AI Haddeler, Garen Chuah, Meng Yee (Michael) You, Yangwei Chan, Jianle Adiwahono, Albertus H. Yau, Wei Yun Chew, Chee-Meng Traversability analysis with vision and terrain probing for safe legged robot navigation |
title | Traversability analysis with vision and terrain probing for safe legged robot navigation |
title_full | Traversability analysis with vision and terrain probing for safe legged robot navigation |
title_fullStr | Traversability analysis with vision and terrain probing for safe legged robot navigation |
title_full_unstemmed | Traversability analysis with vision and terrain probing for safe legged robot navigation |
title_short | Traversability analysis with vision and terrain probing for safe legged robot navigation |
title_sort | traversability analysis with vision and terrain probing for safe legged robot navigation |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441904/ https://www.ncbi.nlm.nih.gov/pubmed/36071857 http://dx.doi.org/10.3389/frobt.2022.887910 |
work_keys_str_mv | AT haddelergaren traversabilityanalysiswithvisionandterrainprobingforsafeleggedrobotnavigation AT chuahmengyeemichael traversabilityanalysiswithvisionandterrainprobingforsafeleggedrobotnavigation AT youyangwei traversabilityanalysiswithvisionandterrainprobingforsafeleggedrobotnavigation AT chanjianle traversabilityanalysiswithvisionandterrainprobingforsafeleggedrobotnavigation AT adiwahonoalbertush traversabilityanalysiswithvisionandterrainprobingforsafeleggedrobotnavigation AT yauweiyun traversabilityanalysiswithvisionandterrainprobingforsafeleggedrobotnavigation AT chewcheemeng traversabilityanalysiswithvisionandterrainprobingforsafeleggedrobotnavigation |