Autonomous Navigation Strategy in Mobile Robot

To solve the navigation problem of mobile robot in unknown environment, a navigation scheme based on bionic strategy was proposed, which simulates operant conditioning mechanism. In this scheme, the tendency cell was designed by use of information entropy, which represents the tendency degree for state. The improved Q learning algorithm used as learning core to direct the learning direction. The Boltzmann machine was used to process annealing calculation, which can randomly selected navigation action. The selected strategy of action will tend to optimal with the learning process. Simulation analyses were carried out in mobile robot; results showed that the proposed method had quick learning velocity and accurate navigation ability, and robot could successfully evade obstacles and arrived at goal point with optimal path.