107 citations · 442 across the 20 of their papers we have counts for
27 papers
PhysibleMDM: Enforcing Inference-Time Physical Feasibility Constraints on Motion Diffusion Models via Noise Optimization
Maximilian Stölzle, David Müller, Agon Serifi +3
Motion Diffusion Models (MDMs) can generate diverse and visually appealing human motion; yet, the resulting trajectories frequently violate physical constraints, limiting their dow…
Walk Like This: Stylized Locomotion for Physics-Based Characters through Example-Driven Diffusion
Joshua Aurand, Agon Serifi, Sammy Christen +4
We present a real-time framework for expressive legged locomotion that enables independent control over velocity and style. Unlike existing data-driven controllers, which typically…
BFMTrack: Latent Sequence Optimization for Physics-Based Motion Tracking with Behavioral Foundation Models
Thomas Rupf, Agon Serifi, David Müller +4
Behavioral Foundation Models (BFMs) offer a promising path toward universal physics-based character control by organizing a rich repertoire of physically plausible behaviors into a…
CoCo-InEKF: State Estimation with Learned Contact Covariances in Dynamic, Contact-Rich Scenarios
Michael Baumgartner, David Müller, Agon Serifi +4
Robust state estimation for highly dynamic motion of legged robots remains challenging, especially in dynamic, contact-rich scenarios. Traditional approaches often rely on binary c…
ReActor: Reinforcement Learning for Physics-Aware Motion Retargeting
David Müller, Agon Serifi, Sammy Christen +3
Retargeting human kinematic reference motion onto a robot's morphology remains a formidable challenge. Existing methods often produce physical inconsistencies, such as foot sliding…
Kamino: GPU-based Simulation of Rigid Multi-Body Physics with Kinematic Loops
Vassilios Tsounis, Guirec Maloisel, Christian Schumacher +6
We present Kamino, a GPU-based physics solver for massively parallel simulations of heterogeneous highly-coupled mechanical systems. Implemented in Python using NVIDIA Warp and int…
Olaf: Bringing an Animated Character to Life in the Physical World
David Müller, Espen Knoop, Dario Mylonopoulos +4
Animated characters often move in non-physical ways and have proportions that are far from a typical walking robot. This provides an ideal platform for innovation in both mechanica…
Robot Crash Course: Learning Soft and Stylized Falling
Pascal Strauch, David Müller, Sammy Christen +4
Despite recent advances in robust locomotion, bipedal robots operating in the real world remain at risk of falling. While most research focuses on preventing such events, we instea…
Attention-Based Map Encoding for Learning Generalized Legged Locomotion
Junzhe He, Chong Zhang, Fabian Jenelten +3
Dynamic locomotion of legged robots is a critical yet challenging topic in expanding the operational range of mobile robots. It requires precise planning when possible footholds ar…
AMOR: Adaptive Character Control through Multi-Objective Reinforcement Learning
Lucas N. Alegre, Agon Serifi, Ruben Grandia +3
Reinforcement learning (RL) has significantly advanced the control of physics-based and robotic characters that track kinematic reference motion. However, methods typically rely on…
On Solving the Dynamics of Constrained Rigid Multi-Body Systems with Kinematic Loops
Vassilios Tsounis, Ruben Grandia, Moritz Bächer
This technical report provides an in-depth evaluation of both established and state-of-the-art methods for simulating constrained rigid multi-body systems with hard-contact dynamic…
Autonomous Human-Robot Interaction via Operator Imitation
Sammy Christen, David Müller, Agon Serifi +5
Teleoperated robotic characters can perform expressive interactions with humans, relying on the operators' experience and social intuition. In this work, we propose to create auton…
Design and Control of a Bipedal Robotic Character
Ruben Grandia, Espen Knoop, Michael A. Hopkins +5
Legged robots have achieved impressive feats in dynamic locomotion in challenging unstructured terrain. However, in entertainment applications, the design and control of these robo…
Perceptive Locomotion through Nonlinear Model Predictive Control
Ruben Grandia, Fabian Jenelten, Shaohui Yang +2
Dynamic locomotion in rough terrain requires accurate foot placement, collision avoidance, and planning of the underactuated dynamics of the system. Reliably optimizing for such mo…
TAMOLS: Terrain-Aware Motion Optimization for Legged Systems
Fabian Jenelten, Ruben Grandia, Farbod Farshidian +1
Terrain geometry is, in general, non-smooth, non-linear, non-convex, and, if perceived through a robot-centric visual unit, appears partially occluded and noisy. This work presents…
Elevation Mapping for Locomotion and Navigation using GPU
Takahiro Miki, Lorenz Wellhausen, Ruben Grandia +3
Perceiving the surrounding environment is crucial for autonomous mobile robots. An elevation map provides a memory-efficient and simple yet powerful geometric representation for gr…
Planar Bipedal Locomotion with Nonlinear Model Predictive Control: Online Gait Generation using Whole-Body Dynamics
Manuel Y. Galliker, Noel Csomay-Shanklin, Ruben Grandia +4
The ability to generate dynamic walking in real-time for bipedal robots with input constraints and underactuation has the potential to enable locomotion in dynamic, complex and uns…
Adaptive CLF-MPC With Application To Quadrupedal Robots
Maria Vittoria Minniti, Ruben Grandia, Farbod Farshidian +1
Modern robotic systems are endowed with superior mobility and mechanical skills that make them suited to be employed in real-world scenarios, where interactions with heavy objects…
Model Predictive Robot-Environment Interaction Control for Mobile Manipulation Tasks
Maria Vittoria Minniti, Ruben Grandia, Kevin Fäh +2
Modern, torque-controlled service robots can regulate contact forces when interacting with their environment. Model Predictive Control (MPC) is a powerful method to solve the under…
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…
Multi-Layered Safety for Legged Robots via Control Barrier Functions and Model Predictive Control
Ruben Grandia, Andrew J. Taylor, Aaron D. Ames +1
The problem of dynamic locomotion over rough terrain requires both accurate foot placement together with an emphasis on dynamic stability. Existing approaches to this problem prior…
Whole-Body MPC and Online Gait Sequence Generation for Wheeled-Legged Robots
Marko Bjelonic, Ruben Grandia, Oliver Harley +3
Our paper proposes a model predictive controller as a single-task formulation that simultaneously optimizes wheel and torso motions. This online joint velocity and ground reaction…
Nonlinear Model Predictive Control of Robotic Systems with Control Lyapunov Functions
Ruben Grandia, Andrew J. Taylor, Andrew Singletary +2
The theoretical unification of Nonlinear Model Predictive Control (NMPC) with Control Lyapunov Functions (CLFs) provides a framework for achieving optimal control performance while…
Feedback MPC for Torque-Controlled Legged Robots
Ruben Grandia, Farbod Farshidian, René Ranftl +1
The computational power of mobile robots is currently insufficient to achieve torque level whole-body Model Predictive Control (MPC) at the update rates required for complex dynami…