Interactive Co-Design of Form and Function for Legged Robots using the Adjoint Method
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Abstract (arXiv)
Our goal is to make robotics more accessible to casual users by reducing the domain knowledge required in designing and building robots. Towards this goal, we present an interactive computational design system that enables users to design legged robots with desired morphologies and behaviors by specifying higher level descriptions. The core of our method is a design optimization technique that reasons about the structure, and motion of a robot in coupled manner in order to achieve user-specified robot behavior, and performance. We are inspired by the recent works that also aim to jointly optimize robot's form and function. However, through efficient computation of necessary design changes, our approach enables us to keep user-in-the-loop for interactive applications. We evaluate our system in simulation by automatically improving robot designs for multiple scenarios. Starting with initial user designs that are physically infeasible or inadequate to perform the user-desired task, we show optimized designs that achieve user-specifications, all while ensuring an interactive design flow.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Jan 2018.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 0; 2025: 2.
4 papers.
- 2021Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Designcited by 38
- 2025Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challengescited by 4
- 2025Toward Humanoid Brain-Body Co-design: Joint Optimization of Control and Morphology for Fall Recoverycited by 2
- 2022Unified Simulation, Perception, and Generation of Human Behaviorcited by 0
- 2025Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges4 Dec 2025
- 2025Toward Humanoid Brain-Body Co-design: Joint Optimization of Control and Morphology for Fall Recovery25 Oct 2025
- 2022Unified Simulation, Perception, and Generation of Human Behavior28 Apr 2022
- 2021Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design7 Oct 2021