What Stands-in for a Missing Tool? A Prototypical Grounded Knowledge-based Approach to Tool Substitution

TL;DR

This paper proposes a grounded knowledge-based method for robot tool substitution in dynamic environments, validated through experiments that closely matched expert choices in most scenarios.

Contribution

It introduces a novel grounded knowledge-based approach for tool substitution and demonstrates its effectiveness through experimental validation.

Findings

Approach matched expert choices in 91% of scenarios

Validated with 22 substitution scenarios

Effective in dynamic, real-world environments

Abstract

When a robot is operating in a dynamic environment, it cannot be assumed that a tool required to solve a given task will always be available. In case of a missing tool, an ideal response would be to find a substitute to complete the task. In this paper, we present a proof of concept of a grounded knowledge-based approach to tool substitution. In order to validate the suitability of a substitute, we conducted experiments involving 22 substitution scenarios. The substitutes computed by the proposed approach were validated on the basis of the experts' choices for each scenario. Our evaluation showed, in 20 out of 22 scenarios (91%), the approach identified the same substitutes as experts.