Analysis and implementation of localization and mapping algorithms for mobile robots based on reconfigurable computing

Localization and Mapping are fundamental problems in the field of mobile robotics that have been receiving considerable attention of the scientific community in the last ten years. Most of the work in this area is developed using personal computers and it still a challenge to execute these algorithms on embedded systems. This paper describes the analysis and embedded implementation of particle filter and occupancy grid algorithms, used for localization and mapping respectively. Experimental results and performance analysis were obtained using the softcore Altera Nios II running on Stratix II FPGA devices.