Design and Simulation Analysis of Simultaneous Localization and Mapping System for Robot Using Multi Photoelectric Sensors

Abstract

Robot technology integrates motion control, information fusion and wireless communication technology. Among them, simultaneous localization and mapping (SLAM) technology is the key to realize robot autonomous navigation. In this exploration, multi photoelectric sensors are used for information fusion to solve the nonlinear and uncertain problems of robot navigation system in obstacle avoidance. The acoustic optical sensor and photoelectric sensor are integrated to collect the information of the surrounding environment. The photoelectric encoder of the drive motor is used to control the direct current machine with fuzzy PID closed-loop control. The methods of extended Kalman filter based SLAM (EKF-SLAM) and particle filter based SLAM (PF-SLAM), which are commonly used in navigation problems, are studied and compared. The proposed SLAM system adopts ARM11 high performance processor structure of S3C6410. ARM processor is responsible for task management, input and output, acoustic optical sensor can provide distance and position information, and photoelectric sensor can provide two-dimensional plane information. Their information fusion helps to restore the three-dimensional information of the environment around the robot. In the simulation analysis, the robot moves in a circular way on the horizontal ground. SLAM algorithm based on the information fusion of multi photoelectric sensors can help the robot better perceive the surrounding environment in unknown environment, increase the movement distance and reduce the overall positioning error; the robot can avoid obstacles well in autonomous mode after hardware and algorithm debugging. In the remote control mode, the movement of the robot can be adjusted by controlling the direction.