A Review on Sensor Technologies, Control Approaches, and Emerging Challenges in Soft Robotics
This review provides an introspective of sensors and controllers in soft robotics. Initially describing the current sensing methods, then moving on to the control methods utilized, and finally ending with challenges and future directions in soft robotics focusing on the material innovations, sensor fusion, and embedded intelligence for sensors and ...
Ean Lovett +5 more
wiley +1 more source
Prediction Error in Quality-Adjusted Life Years in Economic Evaluations of Immune Checkpoint Inhibitors: A Comparison Based on Projected and Observed Updated Survival. [PDF]
Chen J +5 more
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Soft Actuators Integrated with Control and Power Units: Approaching Wireless Autonomous Soft Robots
Soft robots exhibit significant development potential in various applications. However, there are still key technical challenges regarding material improvement, structure design and components integration. This review focuses on the development and challenge of soft actuators, power components, and control components in untethered intelligent soft ...
Renwu Shi, Feifei Pan, Xiaobin Ji
wiley +1 more source
Identify Patients at Risk of HIV Using a Clinical Large Language Model from Electronic Health Records. [PDF]
Liu Y +5 more
europepmc +1 more source
Optical digital twins for disease prevention, diagnosis, therapy, and intervention. [PDF]
Ozcan A +5 more
europepmc +1 more source
PDBFS: A novel active routing protocol for prioritized delivery of safety messages in VANETs. [PDF]
Shah W +6 more
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A Robotic Testing Platform for Pipelined Discovery of Resilient Dielectric Elastomer Actuators. [PDF]
Li AL +10 more
europepmc +1 more source
Human-capital formation: The importance of endogenous longevity. [PDF]
Galama TJ, van Kippersluis H.
europepmc +1 more source
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2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2021Modeling system behavior plays a vital role in controlling systems and in monitoring systems health. Recently the machine learning-enabled modeling technology has become a powerful technique and tool for developing models for explaining, predicting, and describing system behaviors. In particular, the machine learning-enabled predictive modeling methods
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