2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR) 2019
DOI: 10.1109/icorr.2019.8779452
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A Model-Based Method for Minimizing Reflected Motor Inertia in Off-board Actuation Systems: Applications in Exoskeleton Design

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Cited by 7 publications
(4 citation statements)
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References 16 publications
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“…The torque and power output of the system are limited by the servomotor, which is rated for a continuous torque of 49.7 Nm, a peak torque of 143 Nm, and a continuous power output of 5.47 kW. The servomotor was selected using an optimization procedure and dynamical simulations of human walking with robotic assistance at the knee and ankle [31]. Our algorithm iterated over motors from the Kollmorgen catalog and varied mechanical design parameters while minimizing reflected inertia at the prosthesis.…”
Section: A Off-board Actuation and Control Hardwarementioning
confidence: 99%
“…The torque and power output of the system are limited by the servomotor, which is rated for a continuous torque of 49.7 Nm, a peak torque of 143 Nm, and a continuous power output of 5.47 kW. The servomotor was selected using an optimization procedure and dynamical simulations of human walking with robotic assistance at the knee and ankle [31]. Our algorithm iterated over motors from the Kollmorgen catalog and varied mechanical design parameters while minimizing reflected inertia at the prosthesis.…”
Section: A Off-board Actuation and Control Hardwarementioning
confidence: 99%
“…The torque and power output of the system are limited by the servomotor, which is rated for a continuous torque of 49.7 Nm, a peak torque of 143 Nm, and a continuous power output of 5.47 kW. The servomotor was selected using an optimization procedure and dynamical simulations of human walking with robotic assistance at the knee and ankle [36]. Our algorithm iterated over motors from the Kollmorgen catalog and varied mechanical design parameters while minimizing reflected inertia at the prosthesis.…”
Section: A Off-board Actuation and Control Hardwarementioning
confidence: 99%
“…• Secciani et al [87] retrieved the optimal geometrical parameters that allow the kinematics to minimize the error to the desired trajectories of their hand exoskeleton for assistive use; • Kulkarni et al [88] retrieved the optimal link lengths that minimize the difference between the workspace covered by the human and their wrist exoskeleton for assistive use over two joints (one joint is optimized, while the other joint is modeled as an inequality constraint); • Balser et al [90] retrieved the optimal parameters of the cable-driven actuator (i.e., radius, cable, and pulley) and link lengths that minimize the difference between the torques generated by the human and their shoulder exoskeleton for assistive use; • Vazzoler et al [91,92] retrieved the optimal joint spring parameters and positions that minimize the root mean square between joint torques of their leg exoskeleton for assistive use to distribute the weight effectively; • Anderson et al [93] retrieved the optimal "mechanical parameters" (The authors left the description of these mechanical parameters intentionally abstract, and they reported that "the system-specific mechanical design will determine which variables affect the model outputs") that minimize the reflected inertia of their leg exoskeleton for rehabilitation and assistive use; • Kim et al [96] retrieved the optimal position and pressure of pneumatic actuators that minimize the average energy consumption rate of the human joint while running using their leg exoskeleton for assistive use; • Xiao et al [95] retrieved the optimal link lengths and structural angle that minimize the torque exerted by their knee exoskeleton for assistive use; and • Bougrinat et al [97] retrieved the optimal link length and angles that maximize the artificial lever arm (i.e., the perpendicular distance between the joint and the line of action) of their ankle exoskeleton for assistive use.…”
Section: Designs With Other Optimization Techniques (Non-evolutionary)mentioning
confidence: 99%