Title :
Towards geometric decision making in unstructured environments
Author :
Hager, Gregory D.
Author_Institution :
Dept. of Comput. Sci., Yale Univ., New Haven, CT, USA
Abstract :
Presents an approach to sensor-based decision making in unstructured environments that relies on describing geometric structures by parameterized volumes. This approach leads to large systems of nonlinear stochastic inequalities. The author describes how these inequalities can be solved using interval bisection, discusses the structural and statistical convergence of the technique, and presents some preliminary experimental results
Keywords :
convergence; planning (artificial intelligence); robots; statistics; geometric decision making; interval bisection; nonlinear stochastic inequalities; planning; robots; sensor-based decision making; statistical convergence; structural convergence; unstructured environments; Computer science; Convergence; Decision making; Deformable models; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Solid modeling; Stochastic systems; Surface fitting;
Conference_Titel :
Intelligent Robots and Systems '91. 'Intelligence for Mechanical Systems, Proceedings IROS '91. IEEE/RSJ International Workshop on
Conference_Location :
Osaka
Print_ISBN :
0-7803-0067-X
DOI :
10.1109/IROS.1991.174705
