Feature Guided Search for Creative Problem Solving Through Tool Construction
This addresses the challenge of robot adaptation in unforeseen circumstances, specifically for tool use in task planning, but is incremental as it builds on existing heuristic search methods.
The paper tackled the problem of enabling robots to construct missing tools from available objects for task completion, introducing the Feature Guided Search (FGS) algorithm that reduces search effort by approximately 93% compared to standard approaches.
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.