Cristina Garcia Cifuentes — accepted AI-conference papers

2018

Real-Time Perception Meets Reactive Motion Generation

Daniel Kappler, Franziska Meier, Jan Issac, Jim Mainprice, Cristina Garcia Cifuentes, Manuel Wuthrich +4

RA-L 2018

We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models, and hard-to-predict environment dynamics. We quantify the importance of continuous, real-time perception and its tight integration with

Cited by 120 Source ↗Scholar ↗

2017

Probabilistic Articulated Real-Time Tracking for Robot Manipulation

Cristina Garcia Cifuentes, Jan Issac, Manuel Wüthrich, Stefan Schaal, Jeannette Bohg

RA-L 2017

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. This avoids the need for frame transformations when using it in combination with visual object tracking methods. Precision

Cited by 75 Source ↗Scholar ↗

2016

Depth-based object tracking using a Robust Gaussian Filter

Jan Issac, Manuel Wüthrich, Cristina Garcia Cifuentes, Jeannette Bohg, Sebastian Trimpe, Stefan Schaal

ICRA 2016

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 problem. First of all, depth sensors are characterized by fat-tailed measurement noise. To address this issue, we show how

Cited by 86 Source ↗Scholar ↗