A novel hybrid method for mobile robot path planning in unknown dynamic environment based on hybrid DSm model grid map
This study presents a novel hybrid approach for mobile robot aiming to efficiently plan smooth paths in an unknown dynamic environment. The single robot is treated as a multi-agent system, and the corresponding architecture combined with cooperative control is constructed. Then, a new method of information fusion, i.e. Dezert-Smarandache Theory (DSmT) is introduced to build the map of the unknown dynamic environment. Considering the characteristics of sonar sensors, the grid map method is adopted and a sonar sensor mathematical model is constructed based on DSmT. Meanwhile, a few general basic belief assignment functions are constructed to deal with the uncertain, imprecise and sometimes even highly conflicting information obtained by the sonar. Safety guard district search method and an optimising approach for searched paths are proposed. Also, the parameters of internal proportional-integral-derivative controller in the goto agent are adjusted through practical experiments to smooth the path. Finally, two experiments are carried out with mobile robot: one uses the hybrid method, while the other the artificial potential field. The experimental results testify the validity of hybrid DSm model for fusing imprecise information, and also reveal the validity and superiority of the hybrid method for path planning in unknown dynamic environment.
mobile robot path planning multi-agent dezert-smarandache theory a* algorithm