A Co-Design Framework for Energy-Aware Monoped Jumping with Detailed Actuator Modeling

2025-10-07

AI Summary

Existing monopod hopping robot co-design approaches predominantly optimize for a single objective—such as maximum jump height or minimum energy consumption—neglecting the critical trade-off between them. Moreover, they often rely on oversimplified actuator models and omit gearbox parameter optimization, severely limiting design reproducibility and performance fidelity. Method: This paper proposes a novel three-stage co-optimization framework that, for the first time, integrates a high-fidelity motor mass model and explicit gearbox parameter optimization into the co-design process. It simultaneously optimizes mechanical architecture (including geometry and transmission) and control policy, while automatically generating manufacturable, parametric CAD models. The method synergistically combines multi-objective optimization, high-fidelity dynamic simulation, and parametric geometric modeling. Contribution/Results: Experimental evaluation demonstrates a 50% reduction in mechanical energy consumption compared to baseline designs, while reliably achieving a stable 0.8 m jump height—significantly improving both design feasibility and balanced performance across competing objectives.

Technology Category

• Intelligent Robots: Learning & Optimization for ROB
• Search and Optimization: Mixed Discrete/Continuous Search
• Multiagent Systems: Mechanism Design

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

A monoped's jump height and energy consumption depend on both, its mechanical design and control strategy. Existing co-design frameworks typically optimize for either maximum height or minimum energy, neglecting their trade-off. They also often omit gearbox parameter optimization and use oversimplified actuator mass models, producing designs difficult to replicate in practice. In this work, we introduce a novel three-stage co-design optimization framework that jointly maximizes jump height while minimizing mechanical energy consumption of a monoped. The proposed method explicitly incorporates realistic actuator mass models and optimizes mechanical design (including gearbox) and control parameters within a unified framework. The resulting design outputs are then used to automatically generate a parameterized CAD model suitable for direct fabrication, significantly reducing manual design iterations. Our experimental evaluations demonstrate a 50 percent reduction in mechanical energy consumption compared to the baseline design, while achieving a jump height of 0.8m. Video presentation is available at http://y2u.be/XW8IFRCcPgM

Problem

• Optimizing monoped jumping height and energy trade-off
• Incorporating realistic actuator models and gearbox parameters
• Automating CAD generation to reduce manual design iterations

Innovation

• Three-stage co-design optimization for jump height and energy
• Unified framework with realistic actuator and gearbox modeling
• Automated CAD generation for direct fabrication from design