Ng, Mun Kit and Chong, Yung Wey and Ko, Kwang man and Park, Young Hoon and Leau, Yu Beng (2020) Adaptive path finding algorithm in dynamic environment for warehouse robot. Neural Computing and Applications. ISSN 0941-0643
|
Text
Adaptive path finding algorithm in dynamic environment for warehouse robot.pdf Download (2MB) | Preview |
Abstract
Warehouse robots have been widely used by manufacturers and online retailer to automate good delivery process. One of the fundamental components when designing a warehouse robot is path finding algorithm. In the past, many path finding algorithms had been proposed to identify the optimal path and improve the efficiency in different conditions. For example, A* path finding algorithm is developed to obtain the shortest path, while D* obtains a complete coverage path from source to destination. Although these algorithms improved the efficiency in path finding, dynamic obstacle that may exist in warehouse environment was not considered. This paper presents AD* algorithm, a path finding algorithm that works in dynamic environment for warehouse robot. AD* algorithm is able to detect not only static obstacle but also dynamic obstacles while operating in warehouse environment. In dynamic obstacle path prediction, image of the warehouse environment is processed to identify and track obstacles in the path. The image is pre-processed using perspective transformation, dilation and erosion. Once obstacle has been identified using background subtraction, the server will track and predict future path of the dynamic object to avoid the obstacle.
| Item Type: | Article |
|---|---|
| Keyword: | Collision avoidance , Efficiency , Image processing , Robots |
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Department: | FACULTY > Faculty of Computing and Informatics |
| Depositing User: | NORAINI LABUK - |
| Date Deposited: | 16 Apr 2020 11:53 |
| Last Modified: | 17 Apr 2020 23:43 |
| URI: | https://eprints.ums.edu.my/id/eprint/25314 |
Actions (login required)
 |
View Item |