Fuzzy logic based symbolic grounding for best grasp pose for homecare robotics

Symbolic grounding in unstructured environments remains an important challenge in robotics [7]. Homecare robots are often required to be instructed by their human users intuitively, which means the robots are expected to take highlevel commands and execute corresponding tasks in a domestic environment. High-level commands are represented with symbolic terms such as "near" and "close" and, on the other hand, robots are controlled based on trajectories. The robots need to translate the symbolic terms to trajectories. In addition, domestic environment is unstructured where the same objects can be placed in different places over the time. This increases the difficulties in symbolic grounding. This paper presents a fuzzy logic based approach to symbolic grounding. In this approach, grounded concepts are modelled as fuzzy sets and the existing knowledge is used to deduce grounded values given real-time sensory inputs. Experiments results show that this approach works well in unstructured environment.