BLANCHE - AN EXPERIMENT IN GUIDANCE AND NAVIGATION OF AN AUTONOMOUS ROBOT VEHICLE.
IEEE T ROBOTIC AUTOM
193 - 204.
This paper describes the principal components and capabilities of Blanche, an autonomous robot vehicle. Blanche is designed for use in structured office or factory environments rather than unstructured natural environments. This is a significant restriction, but still allows for many potential applications. An overview of the physical configuration of the vehicle is presented as well as a description of its two sensors, an optical rangefinder and odometry. It is assumed that an off-line path planner provides the vehicle with a series of collision-free maneuvers, consisting of line and arc segments, to move the vehicle from a current to a desired position. On board the vehicle, the line and arc segments specifications are sent to control software consisting of low-level trajectory generation and closed-loop motion control. The trajectory generator takes each segment specification and generates a reference vector at each control update cycle. The cart controller controls the front steering angle and drive velocity using conventional feedback compensation to maintain small errors between the reference and measured states.The controller assumes accurate knowledge of the vehicle's position. We believe that position estimation is a primary problem that must be solved for autonomous vehicles working in structured environments. Blanche's position estimation system consists of 1) an a priori map of its environment, represented as a collection of discrete line segments in the plane; 2) a matching algorithm that registers the range data with the map (of line segments) (this algorithm has the properties that it is robust against missing and spurious data and is reasonably fast allowing matching to occur very frequently (approximately every 8 s), and 3) the matching algorithm also estimates the precision of the corresponding match/correction that is then optimally (in a maximum likelihood sense) combined with the current odometric position to provide an improved estimate of the vehicle's position. The vehicle and associated algorithms have all been implemented and tested within a structured office environment.Except for the off-line global path planner, the entire autonomous vehicle is self-contained, all processing being performed on board and with no recourse to passive or active beacons placed in the environment. We believe this vehicle is significant not just because of the sensing and algorithms to be described, but also because its implementation represents a high level of performance at low cost.
|Title:||BLANCHE - AN EXPERIMENT IN GUIDANCE AND NAVIGATION OF AN AUTONOMOUS ROBOT VEHICLE|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
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