Reasoning for Moving Blocks Problem: Formal Representation and Implementation
This work addresses the challenge of commonsense reasoning for robotics, but it is incremental as it applies existing methods to a specific domain.
The paper tackled the problem of representing uncertain, qualitative knowledge for moving blocks tasks by combining Qualitative Reasoning and Probabilistic Functions, formalized using Situation Calculus and implemented in Prolog, achieving successful task completion in most simulated scenarios.
The combined approach of the Qualitative Reasoning and Probabilistic Functions for the knowledge representation is proposed. The method aims at represent uncertain, qualitative knowledge that is essential for the moving blocks task's execution. The attempt to formalize the commonsense knowledge is performed with the Situation Calculus language for reasoning and robot's beliefs representation. The method is implemented in the Prolog programming language and tested for a specific simulated scenario. In most cases the implementation enables us to solve a given task, i.e., move blocks to desired positions. The example of robot's reasoning and main parts of the implemented program's code are presented.