A review of full-stack autonomous obstacle avoidance for assistive robots for the disabled
Yuan Zhang, Shuo Wang, Changlong Zhao, Wei Li, Zhenrong Shi, Meng Liu · 2026
Read A review of full-stack autonomous obstacle avoidance for assistive robots for the disabled by Yuan Zhang, Shuo Wang, Changlong Zhao, Wei Li, Zhenrong Shi, Meng Liu (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13624973.txt.
Description
Robots that help disabled people move safely must dodge obstacles without human steering, and Yuan Zhang and co-authors review the whole technology stack behind that skill. Their survey follows the chain from sensing the environment, through recognising and classifying obstacles, to planning paths and avoiding collisions in real time. Multi-sensor fusion gets special attention for gathering spatial information in complex, changing places.
The review traces detection methods, scene understanding, and judging which ground can be crossed, then compares global planning with local avoidance and newer learning-based approaches. Applications include guide robots for people with visual impairments and smart mobility platforms for wheelchair users, indoors and out. The authors aim to give developers and researchers a reliable base for building assistive robots that support travel and daily life for people with disabilities.
Catalog record
| CREATOR | Yuan Zhang, Shuo Wang, Changlong Zhao, Wei Li, Zhenrong Shi, Meng Liu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 64 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |