Research On Map Building Of Indoor Mobile Robot

The environment modeling of indoor mobile robot is one of the key issues of the current field of robotics. As service robots are applied widely in various industries, indoor mobile robot as a kind of service robots will also be more and more popular. The robot creates the model of the environment by sensing the surrounding environment and its own state, which is the premise and foundation of the robot to complete a variety of more complex tasks.This paper discussed motion control model of wheeled mobile robot firstly and analyzed the reasons of error. Then we discussed localization and map building issues. The robot has an odometer and gyro, after the analysis, we can use the dead reckoning method to get the position with an acceptable error, so the localization is basically solved. Now we focused on the issue of the robot map building in an unknown environment. The complexity of the map building algorithm is proportional to the complexity of the environment and the degree of the algorithm’s autonomy. In the same environment conditions, the more independent of the algorithm the more complex of the algorithm is. Therefore, in order to reduce the complexity of the algorithm, this paper uses a host computer to control the robot to create environment maps. The host computer can control the robot go forward, backward and turn right or left, the computer will record the path the robot go through using the map building algorithm during the moving and make it correspond to the grid map. The robot uses the ultrasonic sensor to detect the boundary of the environment firstly and then users control the robot surround obstacles in the environment. It can create an environment map easily and effectively. This algorithm is experimented on the platform "Future Star" produced by Beijing Bochuang. According to the experiment, the algorithm is easy to operate and achieve, and can create an accurate environment map at the same time. If the localization error can be corrected the accuracy of this algorithm will be further improved.