100 citations · 108 across the 3 of their papers we have counts for
5 papers
Efficient and Accurate Candidate Generation for Grasp Pose Detection in SE(3)
Andreas ten Pas, Colin Keil, Robert Platt
Grasp detection of novel objects in unstructured environments is a key capability in robotic manipulation. For 2D grasp detection problems where grasps are assumed to lie in the pl…
Towards Assistive Robotic Pick and Place in Open World Environments
Dian Wang, Colin Kohler, Andreas ten Pas +4
Assistive robot manipulators must be able to autonomously pick and place a wide range of novel objects to be truly useful. However, current assistive robots lack this capability. A…
Grasp Pose Detection in Point Clouds
Andreas ten Pas, Marcus Gualtieri, Kate Saenko +1
Recently, a number of grasp detection methods have been proposed that can be used to localize robotic grasp configurations directly from sensor data without estimating object pose.…
Learning a visuomotor controller for real world robotic grasping using simulated depth images
Ulrich Viereck, Andreas ten Pas, Kate Saenko +1
We want to build robots that are useful in unstructured real world applications, such as doing work in the household. Grasping in particular is an important skill in this domain, y…
High precision grasp pose detection in dense clutter
Marcus Gualtieri, Andreas ten Pas, Kate Saenko +1
This paper considers the problem of grasp pose detection in point clouds. We follow a general algorithmic structure that first generates a large set of 6-DOF grasp candidates and t…