Research Of Control System Of Sweeping Robot Based On SLAM

The invention of the vacuum cleaner improves people's working conditions and cleaning efficiency.And it reduces people's labor intensity and makes the work of environment cleanning simple and efficient.But the traditional vacuum cleaner still needs human operation and lacks of intelligence.With the continuous progress of science and technology,sweeping robots combi ned with the advantages of vacuum cleaners and robots came into being,from the initial random collision sweeping robot gradually toward the path planning sweeping robot.Based on the rapid development of visual SLAM technology,sweeping robots has become one of the breakthroughs from the laboratory into the market.But now intelligent path planning sweeping robot's prices have been high in the market,and many are foreign products,cheap sweeping robots do not have enough intelligence.In order to reduce the cost of sweeping robots and improve the intelligent degree of random collision sweeping robot and study the application of the popular visual SLAM algorithm,the SLAM-based sweeping robot control system is studied in this paper.According to the service environment and operating requirements,we s elect and improve the relevant algorithm and realize the sweeping robot's environment mapping function and path planning function.In order to solve the problem that the environmental map obtained by LSD-SLAM algorithm is inconsistent with the environment map used in the path planning algorithm,the octomap method and the three-dimensional projection transformation principle are used to realize the map type conversion.On the basis of the grid map,Aiming at the problem that the internal spiral algorithm is easy to fall into the dead zone,the A * algorithm is used to improve it to achieve coverage path planning.In order to verify the practical effect of the algorithm,we design the overall scheme of the control system of the sweeping robot and explain the composition and function of each module of the control system.We select the appropriate hardware equipments according to the function and the requirement,and complete the construction of the control system of the sweeping robot.We complete the calibration of the monocular camera,and carry out the environment modeling experiment and the path planning experiment.It is verified that the maximum relative error of the point cloud map obtained by LSD-SLAM algorithm is 1.36 cm.On the basis of a two-dimensional grid map with a grid length of 14 cm,We conducted point-to-point and full coverage path planning experiments.Point-to-point path planning can make sweeping robots to avoid obstacles and reach the specified location,the repetition rate of the path obtianed by the full coverage path planning is 2.7% and the coverage rate is 100%.