Location and environment modeling method of intelligent movable robot

The invention discloses a location and environment modeling method of an intelligent movable robot, and the method comprises the steps of firstly forming correction iteration expanded Kalman filtering algorithm and determining a number of iterations, then establishing a movement model and an observation model of the movable robot, initializing the status of the movable robot, calculating a position jacobian matrix, controlling and inputting the jacobian matrix to calculate, observing the jacobian matrix and the like; and finally solving a Kalman gain matrix, updating a status estimation equation and a covariance matrix by resolving Kalman gain matrix, and repeating partial steps. The method is centralized on the expanded Kalman filter algorithm which is widely used in the simultaneous location and environment modeling field of the movable robot, and the algorithm is improved, so that the performance of the algorithm is greatly improved, and the algorithm can better meet the application in the SLAM (simultaneous location and mapping). The method also provides powerful technical support for the autonomous navigation and completion of complicated intelligent tasks of the movable robot in an unknown environment.