63 citations · 145 across the 7 of their papers we have counts for
8 papers
RMPflow: A Geometric Framework for Generation of Multi-Task Motion Policies
Ching-An Cheng, Mustafa Mukadam, Jan Issac +4
Generating robot motion for multiple tasks in dynamic environments is challenging, requiring an algorithm to respond reactively while accounting for complex nonlinear relationships…
RMPflow: A Computational Graph for Automatic Motion Policy Generation
Ching-An Cheng, Mustafa Mukadam, Jan Issac +4
We develop a novel policy synthesis algorithm, RMPflow, based on geometrically consistent transformations of Riemannian Motion Policies (RMPs). RMPs are a class of reactive motion…
Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience
Yevgen Chebotar, Ankur Handa, Viktor Makoviychuk +4
We consider the problem of transferring policies to the real world by training on a distribution of simulated scenarios. Rather than manually tuning the randomization of simulation…
Riemannian Motion Policies
Nathan D. Ratliff, Jan Issac, Daniel Kappler +2
We introduce the Riemannian Motion Policy (RMP), a new mathematical object for modular motion generation. An RMP is a second-order dynamical system (acceleration field or motion po…
Real-time Perception meets Reactive Motion Generation
Daniel Kappler, Franziska Meier, Jan Issac +7
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-pred…
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…
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…
Robust Gaussian Filtering using a Pseudo Measurement
Manuel Wüthrich, Cristina Garcia Cifuentes, Sebastian Trimpe +4
Many sensors, such as range, sonar, radar, GPS and visual devices, produce measurements which are contaminated by outliers. This problem can be addressed by using fat-tailed sensor…