Formalising Natural Language Quantifiers for Human-Robot Interactions
This work addresses the challenge of enabling robots to interpret quantifiers in natural language commands, which is an incremental improvement for human-robot interaction systems.
The paper tackled the problem of formalising natural language quantifiers for human-robot interactions by developing a method based on first-order logic with cardinality extensions, resulting in an end-to-end system that processes natural language input to generate logical representations and control a simulated robot.
We present a method for formalising quantifiers in natural language in the context of human-robot interactions. The solution is based on first-order logic extended with capabilities to represent the cardinality of variables, operating similarly to generalised quantifiers. To demonstrate the method, we designed an end-to-end system able to receive input as natural language, convert it into a formal logical representation, evaluate it, and return a result or send a command to a simulated robot.