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Jamming Joints for Stiffness and Posture Control with an Anthropomorphic Hand
- Source :
- RoboSoft
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- Stiffness control is critical in human manipulation. The ability to transition between a low stiffness state, allowing for compliant interactions with the environment, through to rigid states, where it is possible to exert high forces, enables much functionality. Particle jamming provides an elegant method of modulating stiffness online. We develop an un-actuated anthropomorphic hand, with jamming particles enclosed in the joints surrounded by a moulded silicone skin. This approach to stiffness control also allows for control of posture, through 'pre-conditioning' by interacting with the environment in a soft state and then jamming the joints when in a new posture using a single vacuum source and control valve. To demonstrate the capabilities of this new design and fabrication approach, we introduce a 'pre-conditioning' algorithm for exploiting the soft/rigid state transition and environmental interactions to fix the hand in a given demand posture. This approach allows for accurate posture control, which translates to high grasping success rates. In conclusion, we demonstrate the advantages of the new design and fabrication approach, where jamming joints can be used to passively perform a variety of tasks through pre-conditioning of the hand posture. © 2021 IEEE.
- Subjects :
- Anthropomorphic hand
Compliant interaction
Pre-conditioning
Control valves
Computer science
Silicones
Stiffness control
Soft robotics
Environmental interactions
Human manipulation
Stiffness
Jamming
Agricultural robots
Robotics
Computer Science::Robotics
Modulating stiffness
State transitions
Soft state
medicine
medicine.symptom
Control (linguistics)
Simulation
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2021 IEEE 4th International Conference on Soft Robotics (RoboSoft)
- Accession number :
- edsair.doi.dedup.....f23df4c7ec9e23d4e3fadbba6b2546c3
- Full Text :
- https://doi.org/10.1109/robosoft51838.2021.9479352