Publications (5)
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…
The Role of Embodiment in Intuitive Whole-Body Teleoperation for Mobile Manipulation
Sophia Bianchi Moyen, Rickmer Krohn, Sophie Lueth +4
Intuitive Teleoperation interfaces are essential for mobile manipulation robots to ensure high quality data collection while reducing operator workload. A strong sense of embodimen…
AssistDLO: Assistive Teleoperation for Deformable Linear Object Manipulation
Berk Guler, Simon Manschitz, Kay Pompetzki +1
Manipulating Deformable Linear Objects (DLOs) is challenging in robotics due to their infinite-dimensional configuration space and complex nonlinear dynamics. In teleoperation, dep…
A Safety-Aware Shared Autonomy Framework with BarrierIK Using Control Barrier Functions
Berk Guler, Kay Pompetzki, Yuanzheng Sun +2
Shared autonomy blends operator intent with autonomous assistance. In cluttered environments, linear blending can produce unsafe commands even when each source is individually coll…
Constrained Gaussian Process Motion Planning via Stein Variational Newton Inference
Jiayun Li, Kay Pompetzki, An Thai Le +3
Gaussian Process Motion Planning (GPMP) is a widely used framework for generating smooth trajectories within a limited compute time--an essential requirement in many robotic applic…