Title :
Representing partial and uncertain sensorial information using the theory of symmetries
Author_Institution :
Centro Politecnico, Zaragoza Univ., Spain
Abstract :
The author proposes a general model for representing sensorial information and its uncertainty, the symmetries and perturbation model (SPmodel). In the model the intrinsic partiality of geometric information is represented in terms of symmetries of the involved geometric elements. Location uncertainty due to sensor imprecision is represented by means of a local perturbation, expressed in a reference frame attached to the geometric element, with an associated probabilistic model. Using the SPmodel, a method is developed for integrating geometric information that allows estimation of the location of a feature or an object from a set of partial and uncertain observations. The integration mechanisms are based on extended Kalman filter theory
Keywords :
computational geometry; feature extraction; probability; uncertainty handling; SPmodel; extended Kalman filter theory; feature extraction; geometric information; intrinsic partiality; partial observation; probabilistic model; symmetry-perturbation model; uncertain observations; uncertainty; Extremities; Layout; Mobile robots; Robot sensing systems; Robustness; Sensor fusion; Sensor phenomena and characterization; Solid modeling; Uncertainty; Visualization;
Conference_Titel :
Robotics and Automation, 1992. Proceedings., 1992 IEEE International Conference on
Conference_Location :
Nice
Print_ISBN :
0-8186-2720-4
DOI :
10.1109/ROBOT.1992.220119