Spinal-driven locomotion was first hypothesized to exist in biological systems in the 1980s. However, only recently has the concept been applied to legged robots. In implementing spinal-driven locomotion in robots to-date, researchers have focused on bending in the spine. In this article, we propose an additional mode of spinal-driven locomotion: axial torsion via helical actuation patterns. To study torsional spinal-driven locomotion, a six-legged robot with unactuated legs is used. This robot is designed to be modular to allow for changes in the physical system, such as material stiffness of the spine and legs, and has actuators that spiral around the central elastomeric spine of the robot. A model is provided to explain torsional spinal-driven locomotion. Three spinal gaits are developed to allow the robot to walk forward, through which we demonstrate that the speed of the robot can be influenced by the stiffness of the spine and legs. We also demonstrate that a single gait can be used to drive the robot forward and turn the robot left and right by adjusting the leg positions or foot friction. The results indicate that the inclusion of helical actuation patterns can assist in movement. The addition of these actuation patterns or active axial torsion to future, more complex robots with active leg control may enhance the energy efficiency of locomotion or enable fast, dynamic maneuvering.
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http://dx.doi.org/10.1109/lra.2020.2982352 | DOI Listing |
IEEE Robot Autom Lett
July 2020
School of Engineering & Applied Science, Yale University, New Haven, CT 06520 USA.
Spinal-driven locomotion was first hypothesized to exist in biological systems in the 1980s. However, only recently has the concept been applied to legged robots. In implementing spinal-driven locomotion in robots to-date, researchers have focused on bending in the spine.
View Article and Find Full Text PDFFront Public Health
February 2018
Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Assessment of the cortical role during bipedalism has been a methodological challenge. While surface electroencephalography (EEG) is capable of non-invasively measuring cortical activity during human locomotion, it is associated with movement artifacts obscuring cerebral sources of activity. Recently, statistical methods based on blind source separation revealed potential for resolving this issue, by segregating non-cerebral/artifactual from cerebral sources of activity.
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