Aiming at the problem that monocular vision is difficult to adapt to light changes during the indoor positioning of mobile robots, and the cumulative error of odometer leads to positioning errors, a positioning method based on edge measurement and multi-sensor fusion was proposed. Using sparse direct method (semi-direct method) as the front end of monocular vision, real-time monocular camera was used to estimate position and attitude, inertial sensor was used to recovery scale output position information, IMU acceleration, yaw angle and current speed of odometer were obtained. The multiple sensor information was fused through extension Kalman filter algorithm for more precise positioning.The information read by the sensors was processed on the mobile robot side to reduce the robot volume. Edge-side hybrid multi-sensor information fusion enables mobile robots to accurately and real-time complete autonomous positioning in a complex environments even when the sensors are reset and cannot be interfered by human intervention.