A robot agent that can search

Object search is the task of efficiently searching for a given 3D object in a given 3D environment by an agent equipped with a camera for target detection and, if the environment configuration is not known, a method of calculating depth, like a stereo or laser range finder. Sensor planning for object search refers to the task of selecting the sensing parameters so as to bring the target into the field of view of the camera, and to make the image of the target easily detectable by the available recognition algorithms. In this paper, the task of sensor planning for object search is formulated, and a mechanism for this task is proposed. The search space is characterized by the probability distribution of the presence of the target. The goal is to reliably find the desired object with minimum effort. The control of the sensing parameters depends on the current state of the search region and the detecting ability of the recognition algorithm. The huge space of possible sensing actions is decomposed into a finite set of actions that must be considered. In order to represent the surrounding environment of the camera and to efficiently determine the sensing parameters over time, a concept called the sensed sphere is proposed, and its construction is derived.