2 citations · 7 across the 7 of their papers we have counts for
7 papers
Global Tensor Motion Planning
An T. Le, Kay Hansel, João Carvalho +5
Batch planning is increasingly necessary to quickly produce diverse and quality motion plans for downstream learning applications, such as distillation and imitation learning. This…
Machine Learning with Physics Knowledge for Prediction: A Survey
Joe Watson, Chen Song, Oliver Weeger +12
This survey examines the broad suite of methods and models for combining machine learning with physics knowledge for prediction and forecast, with a focus on partial differential e…
Integrating and Evaluating Visuo-tactile Sensing with Haptic Feedback for Teleoperated Robot Manipulation
Noah Becker, Kyrylo Sovailo, Chunyao Zhu +6
Telerobotics enables humans to overcome spatial constraints and physically interact with the environment in remote locations. However, the sensory feedback provided by the system t…
Human Preferences and Robot Constraints Aware Shared Control for Smooth Follower Motion Execution
Qibin Chen, Yaonan Zhu, Kay Hansel +2
With the continuous advancement of robot teleoperation technology, shared control is used to reduce the physical and mental load of the operator in teleoperation system. This paper…
Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation
Yaonan Zhu, Shukrullo Nazirjonov, Bingheng Jiang +6
Vision-based tactile sensors have gained extensive attention in the robotics community. The sensors are highly expected to be capable of extracting contact information i.e. haptic…
Hierarchical Policy Blending As Optimal Transport
An T. Le, Kay Hansel, Jan Peters +1
We present hierarchical policy blending as optimal transport (HiPBOT). HiPBOT hierarchically adjusts the weights of low-level reactive expert policies of different agents by adding…
Hierarchical Policy Blending as Inference for Reactive Robot Control
Kay Hansel, Julen Urain, Jan Peters +1
Motion generation in cluttered, dense, and dynamic environments is a central topic in robotics, rendered as a multi-objective decision-making problem. Current approaches trade-off…