Mapping and path planning for long distance autonomous navigation using multisensory data

This paper presents a methodology and a concept behind the autonomous navigation which can be used in field robots. Long distance navigation in an outdoor environment is a challenging task owing to floor profile variations and slipping problem. The concept is based on SLAM (Simultaneous Localization and Mapping) GMapping algorithm with particle filter approach in mapping process and AMCL (Adaptive Monte Carlo Localization) in navigation process. Experimental results are presented in this paper with the implementation of mobile robot platform using ROS (Robot Operating System). Further, reasons for the errors and methodology to overcome the problems are proposed.