Co-designing versatile quadruped robots for dynamic and energy-efficient motions

This paper presents a concurrent optimization approach for the design and motion of a quadruped in order to achieve energy-efficient cyclic behaviors. Computational techniques are applied to improve the development of a novel quadruped prototype. The scale of the robot and its actuators are optimize...

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Bibliographic Details
Published in:Robotica 2024-06, Vol.42 (6), p.2004-2025
Main Authors: Fadini, Gabriele, Kumar, Shivesh, Kumar, Rohit, Flayols, Thomas, Del Prete, Andrea, Carpentier, Justin, Souères, Philippe
Format: Article
Language:English
Subjects:
Actuators
Co-design
Design optimization
Energy efficiency
Genetic algorithms
Kinematics
Optimization algorithms
Power consumption
Prototypes
Robot dynamics
Robots
Trajectory optimization
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Summary:This paper presents a concurrent optimization approach for the design and motion of a quadruped in order to achieve energy-efficient cyclic behaviors. Computational techniques are applied to improve the development of a novel quadruped prototype. The scale of the robot and its actuators are optimized for energy efficiency considering the complete actuator model including friction, torque, and bandwidth limitations. This method and the optimal bounding trajectories are tested on the first (non-optimized) prototype design iteration showing that our formulation produces a trajectory that (i) can be easily replayed on the real robot and (ii) reduces the power consumption w.r.t. hand-tuned motion heuristics. Power consumption is then optimized for several periodic tasks with co-design. Our results include, but are not limited to, a bounding and backflip task. It appears that, for jumping forward, robots with longer thighs perform better, while, for backflips, longer shanks are better suited. To explore the tradeoff between these different designs, a Pareto set is constructed to guide the next iteration of the prototype. On this set, we find a new design, which will be produced in future work, showing an improvement of at least 52% for each separate task.
ISSN:0263-5747
1469-8668
DOI:10.1017/S0263574724000730