An autonomous vision-based mobile robot

This paper describes the theoretical development and experimental implementation of a complete navigation procedure for use in an autonomous mobile robot for structured environments. Estimates of the vehicle's position and orientation are based on the rapid observation of visual cues located at discrete positions within the environment. The extended Kalman filter is used to combine these visual observations with sensed wheel rotations to produce optimal estimates continuously. The complete estimation procedure, as well as the control algorithm, developed are time independent. A naturally suitable quantity involving wheel rotations is used as the independent variable. One consequence of this choice is that the vehicle speed can be specified independently of the estimation and control algorithms. Reference paths are “taught” by manually leading the vehicle through the desired path. Estimates produced by the extended Kalman filter during this teaching session are then used to represent the geometry of the path. The tracking of taught reference paths is accomplished by controlling the position and orientation of the vehicle relative to the reference path. Time-independence path tracking has necessitated the development of a novel, geometry-based means for advancing along the reference path