Smooth Path Planning of Navigation Robot Based on Improved Ant Colony Algorithm
In order to solve the shortcomings of the traditional ant colony algorithm in the path planning of navigation robot,such as many path inflection points,non-shortest planned path and great blindness of path search,an improved ant colony algo-rithm is proposed.Firstly,the grid map is used to simulate the running environment of the navigation robot,and the 16 direction 24 neighborhood search strategy of two-way search of starting point and ending point is adopted to increase the search direction,ex-pand the search field of ants and improve the global search ability.Then,the information of the starting point,the current node,the next node and the end point is added to the heuristic function to increase the pertinence of searching the path.In addition,pseu-do-random state transition strategy and dynamically adjusted pheromone volatilization coefficient are introduced to improve the con-vergence speed and avoid premature convergence of the algorithm.Finally,cubic B-spline curve is used to smooth the above path.On the simulation platform,compared with other algorithms,the effectiveness and superiority of this algorithm in different complexi-ty environment maps are verified.
mobile robotpath planningant colony algorithmbidirectional path search24 neighborhoods path search
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