Current model free learning-based robot grasping approaches exploit human-labeled
datasets for training the models. However, there are two problems with such a …

This paper surveys recent developments in motion planning and related geometric
algorithms, a theoretical research area that has grown rapidly in response to increasing …

In this paper we tackle the problem of deformable object manipulation through model-free
visual reinforcement learning (RL). In order to circumvent the sample inefficiency of RL, we …

During the past decade, high-performance computer graphics have found application in an
exciting and expanding range of new domains. Among the most dramatic developments has …

What is the right supervisory signal to train visual representations? Current approaches in
computer vision use category labels from datasets such as ImageNet to train ConvNets …

A simple and efficient algorithm is presented, using configuration space, to plan collision-
free motions for general manipulators. An implementation of the algorithm for manipulators …

Recently, end-to-end learning frameworks are gaining prevalence in the field of robot
control. These frameworks input states/images and directly predict the torques or the action …

Since Robotics is the field concerned with the connection of perception to action, Artificial
Intelligence must have a central role in Robotics if the connection is to be intelligent. Artificial …

The synthesis of human hand motion and grasping of arbitrary shaped objects is a very
complex problem. Therefore high-level control is needed to perform these actions. In order …

While obstacles in a robot workspace can effectively reduce the number of degrees of
freedom, there need not be a corresponding loss of functionality for kinematically redundant …