Transformable Quadruped Wheelchairs Capable of Autonomous Stair Ascent and Descent.

mobility challenges reinforcement learning robotic legs and wheels integration stair navigation transformable quadruped wheelchair wheelchair accessibility

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
06 Jun 2024
Historique:
received: 26 04 2024
revised: 27 05 2024
accepted: 04 06 2024
medline: 19 6 2024
pubmed: 19 6 2024
entrez: 19 6 2024
Statut: epublish

Résumé

Despite advancements in creating barrier-free environments, many buildings still have stairs, making accessibility a significant concern for wheelchair users, the majority of whom check for accessibility information before venturing out. This paper focuses on developing a transformable quadruped wheelchair to address the mobility challenges posed by stairs and steps for wheelchair users. The wheelchair, inspired by the Unitree B2 quadruped robot, combines wheels for flat surfaces and robotic legs for navigating stairs and is equipped with advanced sensors and force detectors to interact with its surroundings effectively. This research utilized reinforcement learning, specifically curriculum learning, to teach the wheelchair stair-climbing skills, with progressively increasing complexity in a simulated environment crafted in the Unity game engine. The experiments demonstrated high success rates in both stair ascent and descent, showcasing the wheelchair's potential in overcoming mobility barriers. However, the current model faces limitations in tackling various stair types, like spiral staircases, and requires further enhancements in safety and stability, particularly in the descending phase. The project illustrates a significant step towards enhancing mobility for wheelchair users, aiming to broaden their access to diverse environments. Continued improvements and testing are essential to ensure the wheelchair's adaptability and safety across different terrains and situations, underlining the ongoing commitment to technological innovation in aiding individuals with mobility impairments.

Identifiants

pubmed: 38894465
pii: s24113675
doi: 10.3390/s24113675
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Atsuki Akamisaka (A)

Department of Intelligent Systems, Graduate School of Informatics, Nagoya University, Nagoya 464-8603, Japan.

Katashi Nagao (K)

Department of Intelligent Systems, Graduate School of Informatics, Nagoya University, Nagoya 464-8603, Japan.

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Classifications MeSH