A Co-Design Framework for High-Performance Jumping of a Five-Bar Monoped with Actuator Optimization
This work addresses the challenge of enhancing dynamic jumping in legged robots for applications like robotics and automation, though it is incremental as it extends co-design to include detailed actuator optimization for a specific closed-chain mechanism.
The authors tackled the problem of improving legged robot performance by jointly optimizing mechanical design, actuator parameters, and control for a planar five-bar monoped, achieving a 42% increase in jump distance and a 15.8% reduction in energy consumption compared to a nominal design.
The performance of legged robots depends strongly on both mechanical design and control, motivating co-design approaches that jointly optimize these parameters. However, most existing co-design studies focus on optimizing link dimensions and transmission ratios while neglecting detailed actuator design, particularly motor and gearbox parameter optimization, and are largely limited to serial open-chain mechanisms. In this work, we present a co-design framework for a planar closed-chain five-bar monoped that jointly optimizes mechanical design, motor and gearbox parameters, and control parameters for dynamic jumping. The objective is to maximize jump distance while minimizing mechanical energy consumption. The framework uses a two-stage optimization approach, where actuator optimization generates a mapping from gear ratio to actuator mass, efficiency, and peak torque, which is then used in co-design optimization of the robot design and control using CMA-ES. Simulation results show an improvement of approximately 42% in jump distance and a 15.8% reduction in mechanical energy consumption compared to a nominal design, demonstrating the effectiveness of the proposed framework in identifying optimal design, actuator, and control parameters for high-performance and energy-efficient planar jumping.