Feature Guided Search for Creative Problem Solving Through Tool Construction
arXiv:2008.10685 · doi:10.3389/frobt.2020.592382
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.
arXiv commentNOTE: This paper has been published with Frontiers in Robotics and AI. Please see the following link for the most updated version: https://www.frontiersin.org/articles/10.3389/frobt.2020.592382/full
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Cited by in corpus (4)
- Explainable AI for Robot Failures: Generating Explanations that Improve User Assistance in Fault Recovery
- Creative Problem Solving in Artificially Intelligent Agents: A Survey and Framework
- Feature Guided Search for Creative Problem Solving Through Tool Construction
- Multimodal Coherent Explanation Generation of Robot Failures