Implementing indoor navigation of a mobile robot

This paper describes an implementation of autonomous navigation of a mobile robot indoors. The implementation includes map building, path planning, localization, local path planning and obstacle avoidance, and path tracking. ICP(Iterative closest point) is employed to build grid based map using scanned range data. Dijkstra algorithm plans path from an initial location to a goal position. Particle filter estimates the robot position and orientation using the scanned range data. Elastic force is used for local path planning and obstacle avoidance towards a goal position. The algorithms are combined for autonomous navigation in a work area of 100m×40m, which comprises rooms, corridors, obstacles like passers-by, and many furniture and exhibition area. The robot ran at the maximum speed of 1.0 m/sec, and passed all the way points and reached to goal location through the path of the length 165m in 255 seconds, with the average speed of 0.65m/sec.