133 citations · 237 across the 5 of their papers we have counts for
8 papers
Augmentation for Learning From Demonstration with Environmental Constraints
Xing Li, Manuel Baum, Oliver Brock
We introduce a Learning from Demonstration (LfD) approach for contact-rich manipulation tasks with articulated mechanisms. The extracted policy from a single human demonstration ge…
"The World Is Its Own Best Model": Robust Real-World Manipulation Through Online Behavior Selection
Manuel Baum, Oliver Brock
Robotic manipulation behavior should be robust to disturbances that violate high-level task-structure. Such robustness can be achieved by constantly monitoring the environment to o…
Surprisingly Robust In-Hand Manipulation: An Empirical Study
Aditya Bhatt, Adrian Sieler, Steffen Puhlmann +1
We present in-hand manipulation skills on a dexterous, compliant, anthropomorphic hand. Even though these skills were derived in a simplistic manner, they exhibit surprising robust…
RBO Hand 3 -- A Platform for Soft Dexterous Manipulation
Steffen Puhlmann, Jason Harris, Oliver Brock
We present the RBO Hand 3, a highly capable and versatile anthropomorphic soft hand based on pneumatic actuation. The RBO Hand 3 is designed to enable dexterous manipulation, to fa…
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Nicholas Roy, Ingmar Posner, Tim Barfoot +17
Machine learning has long since become a keystone technology, accelerating science and applications in a broad range of domains. Consequently, the notion of applying learning metho…
The RBO Dataset of Articulated Objects and Interactions
Roberto Martín-Martín, Clemens Eppner, Oliver Brock
We present a dataset with models of 14 articulated objects commonly found in human environments and with RGB-D video sequences and wrenches recorded of human interactions with them…