Abstract
This paper attempts to solve the 2D global path planning problem in a known environment. For this purpose, a smooth path planning method was designed for mobile robots based on dynamic feedback A* search algorithm and the improved ant colony optimization (ACO). Specifically, the ACO was improved from three aspects: optimizing the initial pheromone, improving evolutionary strategy and implementing dynamic closed-loop adjustment of parameters. The planned path was then smoothened by the cubic B-spline curve. The simulation results show our method converged to a shorter path in less time than the original ACO, and avoided the local optimum trap.
| Original language | English |
|---|---|
| Pages (from-to) | 331-336 |
| Number of pages | 6 |
| Journal | Ingenierie des Systemes d'Information |
| Volume | 24 |
| Issue number | 3 |
| DOIs | |
| State | Published - 2019 |
Keywords
- Ant colony optimization (ACO)
- B-spline curve
- Collision-free algorithm
- Path planning