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Robots are increasingly used as scientific tools to investigate animal locomotion. However, designing a robot that properly emulates the kinematic and dynamic properties of an animal is difficult because of the complexity of musculoskeletal systems and the limitations of current robotics technology. Here we propose a design process that combines high-speed cineradiography, optimization, dynamic scaling, 3D printing, high-end servomotors, and a tailored dry-suit to construct Pleurobot: a salamander-like robot that closely mimics its biological counterpart, Pleurodeles waltl. Our previous robots helped us test and confirm hypotheses on the interaction between the locomotor neuronal networks of the limbs and the spine to generate basic swimming and walking gaits. With Pleurobot, we demonstrate a design process that will enable studies of richer motor skills in salamanders. In particular, we are interested in how these richer motor skills can be obtained by extending our spinal cord models with the addition of more descending pathways and more detailed limb central pattern generators (CPG) networks. Pleurobot is a dynamically-scaled amphibious salamander robot with a large number of actuated degrees of freedom (27 in total). Because of our design process, the robot can capture most of the animal’s degrees of freedom and range of motion, especially at the limbs. We demonstrate the robot’s abilities by imposing raw kinematic data, extracted from X-ray videos, to the robot’s joints for basic locomotor behaviors in water and on land. The robot closely matches the behavior of the animal in terms of relative forward speeds and lateral displacements. Ground reaction forces during walking also resemble those of the animal. Based on our results we anticipate that future studies on richer motor skills in salamanders will highly benefit from Pleurobot’s design.
Jonathan Patrick Arreguit O'Neill
Francesco Mondada, Robert Matthew Mills, Rafael Botner Barmak, Raphael Cherfan
Maryam Kamgarpour, Stefana Parascho, Gabriel Rémi Vallat, Anna Maria Maddux, Jingwen Wang