Experiments in integrating constraints with logical reasoning for robotic planning within the twelf logical framework and the prolog language
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The underlying domain of various application areas, especially real-time systems and robotic applications, generally includes a combination of both discrete and continuous properties. In robotic applications, a large amount of different approaches are introduced to solve either a discrete planning or control theoretic problem. Only a few methods exist to solve the combination of them. Moreover, these methods fail to ensure a uniform treatment of both aspects of the domain. Therefore, there is need for a uniform framework to represent and solve such problems. A new formalism, the Constrained Intuitionistic Linear Logic (CILL), combines continuous constraint solvers with linear logic. Linear logic has a great property to handle hypotheses as resources, easily solving state transition problems. On the other hand, constraint solvers deal well with continuous problems defined as constraints. Both properties of CILL gives us powerful ways to express and reason about the robotics domain. In this thesis, we focus on the implementation of CILL in both the Twelf Logical Framework and Prolog. The reader of this thesis can find answers of why classical aspects are not proper for the robotics domain, what advantages one can gain from intuitionism and linearity, how one can define a simple robotic domain in a logical formalism, how a proof in logical system corresponds to a plan in the robotic domain, what the advantages and disadvantages of logical frameworks and Prolog have and how the implementation of CILL can or cannot be done using both Twelf Logical Framework and Prolog.
KeywordsConstrained intuitionistic linear logic
Automated theorem proving
Planning in robotics