Abstract
In order to navigate through unstructured planetary environment autonomously, a path-planning algorithm based on ant colony optimization (ACO), goal-oriented behavior, inertial behavior and obstacle-following behavior are added to ant individual of ACO. By executing behavior weighted fusion, ACO planning algorithm is improved and used to resolve planning problem of planetary rover. Furthermore, a tight-line algorithm is presented, to give a shortest path from start point to the exploration site by processing the path-planning result of ACO. The simulation result shows of the path planning algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 1437-1440 |
| Number of pages | 4 |
| Journal | Kongzhi yu Juece/Control and Decision |
| Volume | 21 |
| Issue number | 12 |
| Publication status | Published - Dec 2006 |
| Externally published | Yes |
Keywords
- ACO
- Behavior fusion
- Lunar rover
- Path-planning
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Yue, F. Z., Cui, P. Y., & Cui, H. T. (2006). Planetary rover path-planning based on ant colony optimization algorithm. Kongzhi yu Juece/Control and Decision, 21(12), 1437-1440.