In order to solve the problem of path planning of tower cranes,an improved ant colony algorithm was proposed.Firstly,the tower crane was simplified into a three-degree-of-freedom mechanical arm,and the D-H motion mode...In order to solve the problem of path planning of tower cranes,an improved ant colony algorithm was proposed.Firstly,the tower crane was simplified into a three-degree-of-freedom mechanical arm,and the D-H motion model was established to solve the forward and inverse kinematic equations.Secondly,the traditional ant colony algorithm was improved.The heuristic function was improved by introducing the distance between the optional nodes and the target point into the function.Then the transition probability was improved by introducing the security factor of surrounding points into the transition probability.In addition,the local path chunking strategy was used to optimize the local multi-inflection path and reduce the local redundant inflection points.Finally,according to the position of the hook,the kinematic inversion of the tower crane was carried out,and the variables of each joint were obtained.More specifically,compared with the traditional ant colony algorithm,the simulation results showed that improved ant colony algorithm converged faster,shortened the optimal path length,and optimized the path quality in the simple and complex environment.展开更多
基金supported by Shaanxi Provincial Key Research and Development Program of China(Nos.2024GX-YBXM-305,2024GX-YBXM-178)Shaanxi Province Qinchuangyuan“Scientists+Engineers”Team Construction(No.2022KXJ032)。
文摘In order to solve the problem of path planning of tower cranes,an improved ant colony algorithm was proposed.Firstly,the tower crane was simplified into a three-degree-of-freedom mechanical arm,and the D-H motion model was established to solve the forward and inverse kinematic equations.Secondly,the traditional ant colony algorithm was improved.The heuristic function was improved by introducing the distance between the optional nodes and the target point into the function.Then the transition probability was improved by introducing the security factor of surrounding points into the transition probability.In addition,the local path chunking strategy was used to optimize the local multi-inflection path and reduce the local redundant inflection points.Finally,according to the position of the hook,the kinematic inversion of the tower crane was carried out,and the variables of each joint were obtained.More specifically,compared with the traditional ant colony algorithm,the simulation results showed that improved ant colony algorithm converged faster,shortened the optimal path length,and optimized the path quality in the simple and complex environment.
