Obstacle avoidance path planning of mobile robot based on improving genetic algorithm
In order to solve the problems of path length,incoherence,redundant turning points and large turn-ing angles,and susceptibility to collisions with obstacles generated by conventional path planning algorithms in a complex and changeable environment,a dynamic obstacle avoidance algorithm based on improved genetic al-gorithm was proposed.An interline random selection strategy and A*algorithm were combined to insert inter-mediate point strategy to improve the initialization algorithm.The safety distance of obstacles was set in the tra-ditional genetic algorithm,and the fitness function was optimized by introducing deletion and optimization op-erators.The dynamic window method combined with the improved genetic algorithm was used to obtain the op-timal path solution.The results show that the path generated by the improved algorithm is smooth;and com-pared with A*algorithm and some improved genetic algorithm,the path is shorter and the number of collisions is less.The improved algorithm has good obstacle avoidance performance in complex dynamic environment,and provides a feasible solution for safe and efficient navigation of mobile robot in real scene.
mobile robotpath planninggenetic algorithmfusion algorithm
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