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Improved ant colony optimization algorithm and its application for path planning of mobile robot in 3-D space

机译:改进的蚁群优化算法及其在3-D空间移动机器人路径规划中的应用

摘要

An improved ant colony algorithm, differential evolution chaos ant colony optimization (DEACO) algorithm, was proposed to plan an optimal collision-free path for mobile robot in 3-D environment. It utilized differential evolution algorithm to update pheromone and chaos disturbance factor was added when pheromone updates for possible stagnation phenomenon. So it enhances escaping capability of algorithm, avoids path-deadlock situations as well as improves the efficiency of planning optimal path. The simulation results indicated that the optimal path on which the robot moves can reach safely and can be rapidly obtained under 3-D space environment, the effect being very satisfactory.
机译:提出了一种改进的蚁群算法,即差分进化混沌蚁群优化算法(DEACO),以规划3-D环境下移动机器人的最优无碰撞路径。它利用差分进化算法更新信息素,并在信息素更新时增加了混沌干扰因子,以防止可能的停滞现象。从而提高了算法的转义能力,避免了路径死锁的情况,提高了规划最优路径的效率。仿真结果表明,机器人运动的最佳路径可以安全地到达,并且在3D空间环境下可以快速获得,效果非常令人满意。

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