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Found 5 papers, 2 papers with code
Data-efficient learning of object-centric grasp preferences
Our pipeline is based on learning a latent space of grasps with a dataset generated with any state-of-the-art grasp generator (e. g., Dex-Net).
First do not fall: learning to exploit a wall with a damaged humanoid robot
This article introduces a method, called D-Reflex, that learns a neural network that chooses this contact position given the wall orientation, the wall distance, and the posture of the robot.
Prescient teleoperation of humanoid robots
Humanoid robots could be versatile and intuitive human avatars that operate remotely in inaccessible places: the robot could reproduce in the remote location the movements of an operator equipped with a wearable motion capture device while sending visual feedback to the operator.
Using exoskeletons to assist medical staff during prone positioning of mechanically ventilated COVID-19 patients: a pilot study
We conducted a pilot study to evaluate the potential and feasibility of back-support exoskeletons to help the caregivers in the Intensive Care Unit (ICU) of the University Hospital of Nancy (France) executing Prone Positioning (PP) maneuvers on patients suffering from severe COVID-19-related Acute Respiratory Distress Syndrome.
A Variational Time Series Feature Extractor for Action Prediction
Our method is based on variational autoencoders.
