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Real-time Grasp Pose Estimation for Novel Objects in Densely Cluttered Environment
In this paper, a real-time grasp pose estimation strategy for novel objects in robotic pick and place applications is proposed.
Robotics Image and Video Processing
Domain Independent Unsupervised Learning to grasp the Novel Objects
In this paper, we present a novel unsupervised learning based algorithm for the selection of feasible grasp regions.
Towards Deep Learning Assisted Autonomous UAVs for Manipulation Tasks in GPS-Denied Environments
In this work, we present a pragmatic approach to enable unmanned aerial vehicle (UAVs) to autonomously perform highly complicated tasks of object pick and place.
