2.3k citations · 4.7k across the 84 of their papers we have counts for
6 papers · 1 filter
Probabilistic Articulated Real-Time Tracking for Robot Manipulation
Cristina Garcia Cifuentes, Jan Issac, Manuel Wüthrich +2
We propose a probabilistic filtering method which fuses joint measurements with depth images to yield a precise, real-time estimate of the end-effector pose in the camera frame. Th…
Latest Datasets and Technologies Presented in the Workshop on Grasping and Manipulation Datasets
Matteo Bianchi, Jeannette Bohg, Yu Sun
This paper reports the activities and outcomes in the Workshop on Grasping and Manipulation Datasets that was organized under the International Conference on Robotics and Automatio…
On the Fundamental Importance of Gauss-Newton in Motion Optimization
Nathan Ratliff, Marc Toussaint, Jeannette Bohg +1
Hessian information speeds convergence substantially in motion optimization. The better the Hessian approximation the better the convergence. But how good is a given approximation…
Automatic LQR Tuning Based on Gaussian Process Global Optimization
Alonso Marco, Philipp Hennig, Jeannette Bohg +2
This paper proposes an automatic controller tuning framework based on linear optimal control combined with Bayesian optimization. With this framework, an initial set of controller…
Interactive Perception: Leveraging Action in Perception and Perception in Action
Jeannette Bohg, Karol Hausman, Bharath Sankaran +4
Recent approaches in robotics follow the insight that perception is facilitated by interaction with the environment. These approaches are subsumed under the term of Interactive Per…
Depth-Based Object Tracking Using a Robust Gaussian Filter
Jan Issac, Manuel Wüthrich, Cristina Garcia Cifuentes +3
We consider the problem of model-based 3D-tracking of objects given dense depth images as input. Two difficulties preclude the application of a standard Gaussian filter to this pro…