Integration, coordination and control of multi-sensor robot systems (sensors, robotics)

Abstract

This thesis develops a theory and methodology for integrating observations from multiple disparate sensor sources. An architecture for a multi-sensor robot system is proposed, based on the idea of a coordinator guiding a group of expert sensor agents, communicating through a blackboard facility. As description of the robot environment is developed in terms of a topological network of uncertain geometric features. Techniques for manipulating, transforming and comparing these representations are described, providing a mechanism for combining disparate observations. A general model of sensor characteristics is developed that describes the dependence of sensor observations on the state of the environment, the state of the sensor itself, and other sensor observations or decisions. A constrained Bayesian decision procedure is developed to cluster and intergrate sparse, partial, uncertain observations from diverse sensor systems. Using the network network topology of the world model, a method is developed for updating uncertain geometric descriptions of the environment in a manner that maintains a consistent interpretation for observations. A team theoretic representation of dynamic sensor operation is used to consider competitive, complementary, and cooperative elements of multi-sensor coordination and control. These descriptions are used to develop algorithms for the dynamic exchange of information between sensor systems and the construction of active sensor strategies. This methodology is implemented on a distributed computer system using an active stereo camera and a robot-mounted tactile gripper.