Colored-object detection for a mobile robot

This paper documents a target acquisition and retrieval problem for a mobile robot. The robot's goal is to grasp a known object whose location is unknown. The robot achieves its goal through a visual search followed by physical movement toward the object. To avoid the computationally expensive, general problem of finding a specific object in a cluttered scene, the robot restricts its visual search area to those places that exhibit colors found on the object. When the object is outside grasping range, precise object world-coordinates are unnecessary for the robot to approach the object. Rough coordinate estimates are sufficient if they are quickly computable and improve with decreasing range. As an example of this problem, a robot is programmed to find and approach a specific soda can at an unknown location in a cluttered environment. Color, in this situation, is a more reliable cue to the location of the can than other features. This paper presents a focus of attention algorithm using color, which provides rough estimates of object position. The algorithm described here is related to the histogram backprojection algorithm of Ballard and Swain, but it does not require the object image size a priori.