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Having a well-rounded fixed leg design for a quadruped inevitably limits performance across diverse tasks, while tunability enables specialization and leads to better performance. This paper introduces a sub-500-gram quadruped robot with a rich leg design space. Made with laminate design and fabrication techniques, its legs have a range of tunable design parameters, including leg length, transmission ratio, and passive parallel and series stiffness. The legs are also straightforward to model, low-cost, and fast to manufacture. We propose methods to span the leg’s feasible design space and construct simulation environments for training a locomotion policy with reinforcement learning to remove the need for manual controller design and tuning. This policy not only works across leg designs but also exploits the unique dynamics of each leg for better locomotion. A curation process is employed to select designs given performance goals, which is more interpretable than optimization and provides insights for design improvements and discoveries of design principles. Thanks to the tight integration of design, fabrication, simulation, and control, our proposed pipeline produces leg designs with performance that aligns with the simulation, while the learned locomotion policy can be used successfully on the real robot. The fast longitudinal running design reaches a maximum speed of 0.7 m/s or 5.4 body lengths per second, and the low cost of transport (COT) design has a COT of 0.3.
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Development of A Dynamic Quadruped with Tunable, Compliant Legs
To facilitate the study of how passive leg stiffness influences locomotion dynamics and performance, we have developed an affordable and accessible 400 g quadruped robot driven by tunable compliant laminate legs, whose series and parallel stiffness can be easily adjusted; fabrication only takes 2.5 hours for all four legs. The robot can trot at 0.52 m/s or 4.4 body lengths per second with a 3.2 cost of transport (COT). Through locomotion experiments in both the real world and simulation we demonstrate that legs with different stiffness have an obvious impact on the robot’s average speed, COT, and pronking height. When the robot is trotting at 4 Hz in the real world, changing the leg stiffness yields a maximum improvement of 37.1% in speed and 62.0% in COT, showing its great potential for future research on locomotion controller designs and leg stiffness optimizations.
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- Award ID(s):
- 1944789
- PAR ID:
- 10509545
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- ISBN:
- 978-1-6654-9190-7
- Page Range / eLocation ID:
- 495 to 502
- Format(s):
- Medium: X
- Location:
- Detroit, MI, USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/IROS55552.2023.10342283
