A5013062127- Soft Robotics and Applications
- Advanced Materials and Mechanics
- Robot Manipulation and Learning
- Modular Robots and Swarm Intelligence
- Stroke Rehabilitation and Recovery
- Prosthetics and Rehabilitation Robotics
- Robotic Locomotion and Control
- Teleoperation and Haptic Systems
Northwestern University
2022-2024
McCormick (United States)
2024
To advance the design space of electrically‐driven soft actuators, a flexible, architected robotic actuator is presented for motor‐driven extensional motion. The comprises 3D printed, cylindrical handed shearing auxetic (HSA) structure and deformable, internal rubber bellows shaft. linearly extends upon applying torque from servo motor; shaft stretchable but resistant to torsional deflection, allowing it transmit motor other end HSA. high flexibility HSA enable adaptively extend even when...
Untethered operation remains a fundamental challenge in soft robotics. Soft robotic actuators are generally unable to produce the forces required for carrying essential power and control hardware on-board. Moreover, current untethered robots often have low operating times given actuators' limited efficiency lifetime. Here, we 3D print cylindrical handed shearing auxetics (HSAs) from single-cure polyurethane resins use as scalable, motorized machines. Mechanical characterization of individual...
Gait generation for soft robots is challenging due to the nonlinear dynamics and high dimensional input spaces of actuators. Limitations in robotic control perception force researchers hand-craft open loop controllers gait sequences, which a non-trivial process. Moreover, short actuator lifespans natural variations behavior limit machine learning techniques settings that can be learned on same time scales as robot deployment. Lastly, simulation not always possible, heterogeneity nonlinearity...
Gait generation for soft robots is challenging due to the nonlinear dynamics and high dimensional input spaces of actuators. Limitations in robotic control perception force researchers hand-craft open loop controllers gait sequences, which a non-trivial process. Moreover, short actuator lifespans natural variations behavior limit machine learning techniques settings that can be learned on same time scales as robot deployment. Lastly, simulation not always possible, heterogeneity nonlinearity...