Functional understanding of space : Representing spatial knowledge using concepts grounded in an agent's purpose
Kristoffer Sjöö · 2011
This thesis examines the role of function in representations of space by robots – that is, dealing directly and explicitly with those aspects of space and objects in space that serve some purpose for the robot. It is suggested that taking function into account helps increase the generality and robustness of solutions in an unpredictable and complex world, and the suggestion is affirmed by several instantiations of functionally conceived spatial models. These include perceptual models for the “on ” and “in ” relations based on support and containment; context-sensitive segmentation of 2-D maps into regions distinguished by functional criteria; and, learned predictive models of the causal relationships between objects in physics simulation. Practical application of these models is also demonstrated in the context of object search on a mobile robotic platform. Acknowledgements I have many people to thank for all of the help, criticism, cooperation, encouragement, inspiration and (not to forget) financial support that has been instrumental in the writing of this thesis and the research and related work that has led up to it. So many, in fact, that I’m certain to forget to mention some – thus, if you, reading this, should feel that you have been unduly left out in the following, please tell me so and I will buy you a drink. All the work for this thesis has been carried out at the Centre for Autonomous