An UAV Path Planning Method Based on Improved Artificial Bee Colony Algorithm
To find the optimal path of UAV in multi obstacle environment efficiently and accurately,an improved artificial bee colony algorithm(GWOABC)is proposed.Firstly,a mathematical model is constructed according to the UAV path planning environ-ment for simulation.Secondly,in order to improve traditional artificial bee colony algorithm's search rules and honey source selec-tion method,GWOABC algorithm introduces the idea of Gray Wolf algorithm,a new dynamic evaluation rule and cauchy mutation strategy.Finally,in order to verify the effectiveness of GWOABC algorithm,20 comparative experiments are carried out.The experi-mental results show GWOABC algorithm's convergence speed,convergence accuracy and robustness are better than those of the comparison algorithm,and the path planned by GWOABC algorithm is better and safer.
UAVgray wolf algorithmartificial bee colony algorithmCauchy mutationpath planning
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