Research On Obstacle Avoidance Technology Of Cleaning Robot Based On Multi-sensor

Realizing non-collision navigation for mobile robot under the non-structured environment is currently a big hot spot, and is also a big difficulty. The dissertation take cleaning robot as the object of study, it designed a multi-sensor hardware system based on the cleaning robot platform and formed a new robot. Then a neurofuzzy-Based method was transplanted into the robot. Some theory explorations about localization were made upon our robot at last:Firstly, the dessertation designed a new multi-sensor from reality, and connected the new system to cleaning robot substitute the beforhand foresight board, the new system including 15 ultrasonic sensors, may survey the barrier distance of 5-50cm in 14 direction, then 8 pair of infrared sensors have been inserted in the middle of ultrasonic sensors, the infrared sensor can survey the obstacle of 5cm in 8 direction. Therefor, the new system can guarantee the robot to obtain the majority of obstacle distance and the azimuth information in the half-turn. At the same time, the dissertation has studied each kind of ultrasonic ranging algorithm, as well as the ultrasonic sensor and infrared sensor range finder's some characteristics, making the multi-sensor systems be able to obtain the best survey effect.Secondly, the robot need a proper obstacle avoidance method since it work under a very complex environment, so the dissertation studied many localization algorithm based on multi-sensor hardware. Enormous accumulated error was existed in dead reckoning algorithm based on the electro-optical encoder, so we introduced EKF (Expanded Kalman Filtering) algorithm to fusion electro-optical encoder's feedback data and the range finder sensor's observation data to adjust the error, which can obtain very satisfactory localization effect. However, EKF method would get a worse effect in an environment with very strong nonlinear, which can be well substitued by UKF (Unscented Kalman Filtering) method.Finally, the dissertation did some research about obstacle avoidance algorithm based on the new platform, figured a neurofuzzy-based method which can be applicated on cleaning robot. The method takes the distance imformation of obstacle, speed of itself and the angle between itself and goal as input, and wheel's addition and subtraction speed as the output. It could make robot avoid abstacle quite well in unknown environment. The dissertation determined the basic parameter of the method through thoery simulation, and adjusted the parameter through neural network training. The module with certain parameter was finally transplanted to cleaning robot which can easily avoid obastacle in experiment.