Research on intelligent pharmacy unmanned delivery vehicle path planning and drug recognition technology based on JPS and RRT algorithms
Hengzhe Yue, Kun Cao, Zhaokun Yang, Quntao An, Lizhi Sun · 2025
Read Research on intelligent pharmacy unmanned delivery vehicle path planning and drug recognition technology based on JPS and RRT algorithms by Hengzhe Yue, Kun Cao, Zhaokun Yang, Quntao An, Lizhi Sun (2025) 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-12830942.txt.
Description
Hengzhe Yue, Kun Cao, Zhaokun Yang, Quntao An, and Lizhi Sun improve a drug delivery robot for a smart pharmacy, in work from 2025. The robot must plan routes through the pharmacy and recognize the right drug packs. Classic path methods can be slow or trap the robot in dead ends.
The team merged two search algorithms to plan paths more exactly. A neural network fit to map images, with thresholds to cut errors, sharpened the map. For drug recognition they used a contour based method with a matching algorithm to find drug type and position. Planning time and path quality both beat classic methods in their tests.
Catalog record
| CREATOR | Hengzhe Yue, Kun Cao, Zhaokun Yang, Quntao An, Lizhi Sun |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 256 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |