Abstract
As a vital part of autonomous navigation of mobile robot, path planning is a hot research direction which aims at searching a shortest collision-free path from the starting position to the goal position in a complex environment. In this paper, a method for global dynamic path planning is designed based on improved self-adaptive harmony search algorithm (ISAHS) and Morphin algorithm. Firstly, to improve the quality of new solution vector, a neighbors and optimal learning strategy is introduced. Secondly, two key parameters are adjusted adaptively and a probability disturbance strategy is designed for renewing harmony memory, and then an improved self-adaptive harmony search algorithm is proposed to obtain an initial optimal path in the static environment. Finally, the Morphin algorithm is introduced to avoid the moving obstacles in real time. Simulation results indicate that the proposed method performs well in planning an initial static optimal path and it can avoid all preset moving obstacles effectively.
Highlights
Mobile robot is one of the most intelligent devices which can replace humans to do repetitive and dangerous jobs [1,2]
Some new intelligence optimization algorithms have performed excellently in solving path planning problem such as genetic algorithm (GA) [14,15], particle swarm optimization (PSO) [16], differential evolutionary algorithm (DE) [17] and firework algorithm (FWA) [18]. [19], Li and Chou designed a self-adaptive learning particle swarm optimization (SLPSO) which selects the most appropriate search strategy adaptively in different stages and limits particle velocity and position according to the boundary violation strategy
WORK A global dynamic path planning method based on improved self-adaptive harmony search algorithm (ISAHS) and Morphin algorithm is proposed in this paper
Summary
Mobile robot is one of the most intelligent devices which can replace humans to do repetitive and dangerous jobs [1,2]. The main contributions of this paper are as follows: (i) a global dynamic path planning method based on improved self-adaptive harmony search algorithm (ISAHS) and Morphin algorithm under dynamic environment is proposed. A. ISAHS AGORITHM In this paper, an improved self-adaptive harmony search algorithm (ISAHS) is designed to obtain an initial optimal path in the static environment. At the beginning of optimization, the new solution vector is mainly composed of random mutation due to the smaller HMCR, which is beneficial to the richness of harmony memory and global search ability. We search an initial optimal path in the static environment according to ISAHS and the Morphin algorithm is used to avoid the moving obstacles in real time.
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