| With the development of science and technology,the intelligent sweeping robot with multiple sensors can be used to clean the ground of home and public places instead of people.Because it can improve the efficiency of cleaning work and has low price,it has been widely recognized by people and has broad market prospects.The control system of intelligent sweeping robot must have high reliability and practicability.At the same time,global path planning is also one of the important indexes to evaluate the performance of sweeping robot,which marks the intelligent level of intelligent sweeping robot.Global path planning requires the intelligent sweeping robot to plan a path that is as non repetitive as possible and covers all the sweepable areas.The existing sweeping robot has single function,easy to collide with obstacles,low coverage and high repetition rate,so the research on path planning of sweeping robot is very important.As a common path planning method for mobile robot,ant colony algorithm has good search ability,so it has great practical significance to apply it to intelligent sweeping robot.This paper first studies the mechanical structure of intelligent sweeping robot at home and abroad,and designs the experimental platform of intelligent sweeping robot.Its main functions include the perception of collision,fall and other emergency states,the acquisition of sweeping robot’s own running speed and posture information,ground cleaning,fan cleaning,motion execution and so on.Select a variety of sensor fusion circuit design and design the driver software to achieve the function.With stm32f103zet6 as the main control chip,the main control module is responsible for the hardware logic control and software planning of the whole system;the information acquisition module is composed of ultrasonic sensor,infrared sensor,collision switch,mpu6050 sensor and photoelectric encoder,which is responsible for the collection of robot’s own state and environmental information;various mechanical devices and their driving circuits are the main structure The implementation module is responsible for specific cleaning tasks.Secondly,this paper uses the grid method to model the environment map.Considering the low efficiency in solving the path planning problem in complex environment,this paper proposes to use bousrtophedon decomposition method to decompose and number the grid map,decompose the feasible region into sub regions,and then use ant colony algorithm to optimize the path of the divided grid region,which makes the ant colony algorithm more efficient The total efficiency of the method has been greatly improved.In the use of ant colony algorithm for path planning,considering that the ant colony algorithm is easy to fall into the local optimal solution,the number of iterations is more,the length of the search path is longer and so on,this paper continues to propose an improved ant colony algorithm,using the optimization of pheromone Volatilization Coefficient,improved state transition probability formula,adding ant fallback strategy to improve the algorithm,and simulation with software The results show that the ability and efficiency of the algorithm are improved.Finally,the key functions of the intelligent sweeping robot platform are tested to verify the feasibility and rationality of the program design.The designed intelligent sweeping robot platform is tested in the actual application scene,and the improved ant colony algorithm is used to make path planning to verify its feasibility.The laser tracker is used to collect the environmental position information of the sweeping robot in real time,and the data is imported into Matlab for processing and calculation,and the sweeping coverage rate and repetition rate are obtained.Comprehensive simulation results show that the proposed method can effectively realize the global path planning of intelligent sweeping robot. |
