Abstract
The obstacle avoidance in path planning, a hot topic in mobile robot control, has been extensively investigated. The existing ant colony algorithms, however, remain as drawbacks including failing to cope with narrow aisles in working areas, large amount of calculation, etc. To address above technical issues, an improved ant colony algorithm is proposed for path planning. In this paper, a new weighted adjacency matrix is presented to determine the walking direction and the narrow aisles therefore are avoided by redesigning the walking rules. Also, the best ant and the worst ant are introduced for the adjustment of pheromone to facilitate the searching process. The proposed algorithm guarantees that robots are able to find a satisfying path in the presence of narrow aisles. The simulation results show the effectiveness of the proposed algorithm.
Highlights
The past decades have witnessed a rapid development of the robot control
At the aspect of path planning, much of work concentrates on artificial potential field method [1], ant colony algorithm [2], and genetic algorithm [3]
Aiming at the convergence speed of ant colony algorithm and the problem of easy to fall into local optimum, [4] proposes to add artificial local potential optimization algorithm for specific problems in the ant colony algorithm search process, which reduces the blindness of ant colony algorithm and enhances search capabilities
Summary
The past decades have witnessed a rapid development of the robot control. Nowadays, robots are expected to be capable of various tasks, e.g., collecting the environmental information, avoiding obstacles accurately, fast path planning, etc. In spite of the considerable achievement of the ant colony algorithm in dealing with path planning, one may notice that some flaws remain, including exponential explosion [8] and failure of bypassing narrow aisle [9]. Some articles propose the approaches of environment map reconstruction, where an obstacle is intentionally mapped to occupy one or more grids. According to the different positions of the obstacles, the corresponding modes of bypass are defined, respectively Both of the methods are aiming at bypassing the narrow aisle, the performance is of conservativeness. The directions of motion of a robot are expanded to eight and the movement direction of the robot is analyzed for different positions, an improved ant colony algorithm is proposed by setting new walking rules. The contribution of this paper can be summarized as the following aspects. (a) The outwards of grids are extended to eight directions for a better path plan. (b) The new walking rules were proposed for bypassing the narrow aisle. (c) The amount of calculation is reduced by proposing analytical calculation method
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