| Garage inspection is an important operation to ensure the safety and stability of the car park.At present,most garages are still mainly inspected manually,i.e.staff check the garage environment with a familiar inspection path at regular intervals,which is timeconsuming and laborious and can easily cause irreparable damage due to staff negligence.With the development and maturity of robotics,intelligent inspection robots have become the new assistant for garage patrol management.The key to robotic inspection is to find an optimal and safe path from source to destination by reasonably avoiding static and dynamic obstacles such as cars and pedestrians.Considering the complex environment and inspection needs of garages,this paper carries out research on path planning methods for inspection robots so that mobile robots can carry out safe and efficient,low energyconsuming garage inspection tasks with good materiality and reliability according to the established inspection path,and constructs a robot system for verification.The details are as follows:(1)To address the shortcomings of the ant colony algorithm in global path planning,such as the ease of falling into local optimum and poor convergence of the preliminary search,the randomness of the algorithm is increased by introducing adaptive adjustment of the pheromone volatility coefficient;the pheromone matrix of garage direction is established by fusing the angle parameters based on the garage topology map;the artificial potential field force improvement heuristic function is added to make the pheromone tend to spread in the direction of the potential field force to the higher adaptation value of the subspace.The simulation results show that the improved algorithm can effectively reduce the path cost and improve the search efficiency in different scenarios.(2)To address the situation that in local path planning,the dynamic window method cannot be used alone due to the lack of global information,insufficient foresight and the decision path is not the global optimal path,an improved dynamic window method based on the elliptic equation of the obstacle distance evaluation subfunction is proposed to increase the obstacle avoidance weight by applying the elliptic-shaped distance to avoid obstacles at a safer distance and extract the optimal path node of the improved ant colony algorithm path nodes as new path evaluation sub-functions to maintain the optimality of dynamic planning under the constraint of global paths.The simulation results show that the paths planned by the improved algorithm are better able to cope with sudden dynamic and static obstacles than those planned by the traditional algorithm,and better meet the dynamic planning requirements of the garage inspection robot under the influence of multiple environmental factors in the actual operation process.(3)In order to meet the actual inspection needs of the garage,an intelligent inspection robot equipment and system for the garage have been developed.Combined with scheme design,software and hardware development,and experimental testing and verification,the effectiveness and practical application of the fusion algorithm in this paper have been further verified in real garage and simulation environments.The results show that the inspection robot can effectively avoid pedestrians and vehicles that randomly appear in the garage,find the shortest inspection path,and meet the requirements of actual inspection indicators. |
