Decision-making under severe uncertainty for autonomous mobile robots

The field of robotics is on a growth curve, with most of the growth expected in the areas of personal and service robots. As robots become more prevalent in chaotic home and industrial settings, they will be required to make increasingly independent decisions about how to accomplish their tasks. A key to accomplishing this is the development of techniques to allow robots to handle severe uncertainty. This paper introduces the use of information gap theory as a way to enable robots to make robust decisions in the face of uncertainty, and illustrates this with an example problem.