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Found 4 papers, 3 papers with code
Deep Functional Predictive Control for Strawberry Cluster Manipulation using Tactile Prediction
Pushing an object with a robot finger along a desired trajectory in 3D is a highly nonlinear and complex physical robot interaction, especially when the object is not stably grasped.
Action Conditioned Tactile Prediction: a case study on slip prediction
We compare the performance of these models with those of our proposed models.
Deep Movement Primitives: toward Breast Cancer Examination Robot
This paper presents a novel approach to manipulation path/trajectory planning called deep Movement Primitives that successfully generates the movements of a manipulator to reach a breast phantom and perform the palpation.
A data-set of piercing needle through deformable objects for Deep Learning from Demonstrations
Our study indicates RCNs improve the prediction accuracy of the model despite that the baseline feed-forward CNNs successfully learns the relationship between the visual information and the next step control actions of the robot.
