Feature Guided Search for Creative Problem Solving Through Tool Construction

TL;DR

This paper presents the Feature Guided Search algorithm that enables robots to efficiently construct tools from available objects by considering physical attributes, significantly reducing search effort in task planning.

Contribution

The paper introduces FGS, a novel heuristic search method that incorporates physical object features for effective tool construction in robotic task planning.

Findings

FGS reduces search effort by approximately 93%.

Enables robots to adapt to unforeseen circumstances by constructing tools.

Improves efficiency of tool construction in robotic applications.

Abstract

Robots in the real world should be able to adapt to unforeseen circumstances. Particularly in the context of tool use, robots may not have access to the tools they need for completing a task. In this paper, we focus on the problem of tool construction in the context of task planning. We seek to enable robots to construct replacements for missing tools using available objects, in order to complete the given task. We introduce the Feature Guided Search (FGS) algorithm that enables the application of existing heuristic search approaches in the context of task planning, to perform tool construction efficiently. FGS accounts for physical attributes of objects (e.g., shape, material) during the search for a valid task plan. Our results demonstrate that FGS significantly reduces the search effort over standard heuristic search approaches by approximately 93% for tool construction.