Publications (8)
Contact-Implicit Trajectory Optimization for Dynamic Object Manipulation
Jean-Pierre Sleiman, Jan Carius, Ruben Grandia +2
We present a reformulation of a contact-implicit optimization (CIO) approach that computes optimal trajectories for rigid-body systems in contact-rich settings. A hard-contact mode…
TacSL: A Library for Visuotactile Sensor Simulation and Learning
Iretiayo Akinola, Jie Xu, Jan Carius +2
For both humans and robots, the sense of touch, known as tactile sensing, is critical for performing contact-rich manipulation tasks. Three key challenges in robotic tactile sensin…
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
Marco Tranzatto, Frank Mascarich, Lukas Bernreiter +38
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy h…
Whole-Body Nonlinear Model Predictive Control Through Contacts for Quadrupeds
Michael Neunert, Markus Stäuble, Markus Giftthaler +5
In this work we present a whole-body Nonlinear Model Predictive Control approach for Rigid Body Systems subject to contacts. We use a full dynamic system model which also includes…
Imitation Learning from MPC for Quadrupedal Multi-Gait Control
Alexander Reske, Jan Carius, Yuntao Ma +2
We present a learning algorithm for training a single policy that imitates multiple gaits of a walking robot. To achieve this, we use and extend MPC-Net, which is an Imitation Lear…
Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning
NVIDIA, :, Mayank Mittal +104
We present Isaac Lab, the natural successor to Isaac Gym, which extends the paradigm of GPU-native robotics simulation into the era of large-scale multi-modal learning. Isaac Lab c…