Fuzzy optimisation based symbolic grounding for service robots

Abstract

Symbolic grounding is a bridge between high-level planning and actual robot sensing, and actuation. Uncertainties raised by the unstructured environment make a bottleneck for integrating traditional artificial intelligence with service robotics. This paper presents a fuzzy logic based approach to formalise the grounding problems into a fuzzy optimization problem, which is robust to uncertainties. Novel techniques are applied to establish the objective function, to model fuzzy constraints and to perform fuzzy optimisation. The outcome is tested with a service robot fetch and carry task, where the fuzzy optimisation approach helps the robot to determine the most comfortable position (location and orientation) for grasping objects. Experimental results show that the proposed approach improves the robustness of the task implementation in unstructured environments.