A method for solving TSP of steel pylon inspection by magnetic adsorption robots based on improved ant colony optimization

For the problem of multi-point inspection of steel pylons by robots for very large bridges, the input inspection path points are abstracted as nodes and the weight of each path point is calculated according to the actual situation of the project, so as to establish a weighted undirected graph of the movement of magnetic adsorption robots between each point. The original problem can then be transformed into the problem of finding the shortest possible path (the minimum cost) for each node in a given group, visiting each node once and returning to the origin, namely the traveling salesman problem (TSP). In this study, a path optimization method for magnetic adsorption robots for steel pylons based on an improved ant colony optimization (ACO) algorithm is proposed, and the Euclidean TSP is solved using the improved ACO approach (IACO). Finally, the simulation results demonstrate that IACO has advantages in convergence speed and stability as compared to conventional ACO, which proves the validity of the proposed method.