Learning to Design and Use Tools for Robotic ManipulationDownload PDF

Published: 30 Aug 2023, Last Modified: 16 Oct 2023CoRL 2023 PosterReaders: Everyone
Keywords: tool use, manipulation, design
TL;DR: We propose a framework for robots to design tools and perform manipulation with them based on the task at hand.
Abstract: When limited by their own morphologies, humans and some species of animals have the remarkable ability to use objects from the environment toward accomplishing otherwise impossible tasks. Robots might similarly unlock a range of additional capabilities through tool use. Recent techniques for jointly optimizing morphology and control via deep learning are effective at designing locomotion agents. But while outputting a single morphology makes sense for locomotion, manipulation involves a variety of strategies depending on the task goals at hand. A manipulation agent must be capable of rapidly prototyping specialized tools for different goals. Therefore, we propose learning a designer policy, rather than a single design. A designer policy is conditioned on task information and outputs a tool design that helps solve the task. A design-conditioned controller policy can then perform manipulation using these tools. In this work, we take a step towards this goal by introducing a reinforcement learning framework for jointly learning these policies. Through simulated manipulation tasks, we show that this framework is more sample efficient than prior methods in multi-goal or multi-variant settings, can perform zero-shot interpolation or fine-tuning to tackle previously unseen goals, and allows tradeoffs between the complexity of design and control policies under practical constraints. Finally, we deploy our learned policies onto a real robot. Please see our supplementary video and website at https://robotic-tool-design.github.io/ for visualizations.
Student First Author: yes
Supplementary Material: zip
Instructions: I have read the instructions for authors (https://corl2023.org/instructions-for-authors/)
Video: https://robotic-tool-design.github.io/
Website: https://robotic-tool-design.github.io/
Publication Agreement: pdf
Poster Spotlight Video: mp4
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