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Grasping Using Tactile Sensing and Deep Calibration
Tactile perception is an essential ability of intelligent robots in interaction with their surrounding environments.
Edge-Based Recognition of Novel Objects for Robotic Grasping
In this paper, we investigate the problem of grasping novel objects in unstructured environments.
From virtual demonstration to real-world manipulation using LSTM and MDN
Our experimental studies validate the three contributions of the paper: (1) the controller learned from virtual demonstrations can be used to successfully perform the manipulation tasks on a physical robot, (2) the LSTM+MDN architectural choice outperforms other choices, such as the use of feedforward networks and mean-squared error based training signals and (3) allowing imperfect demonstrations in the training set also allows the controller to learn how to correct its manipulation mistakes.
