630 citations · 1.2k across the 74 of their papers we have counts for
10 papers · 1 filter
Variational Integrators and Graph-Based Solvers for Multibody Dynamics in Maximal Coordinates
Jan Brüdigam, Stefan Sosnowski, Zachary Manchester +1
Multibody dynamics simulators are an important tool in many fields, including learning and control for robotics. However, many existing dynamics simulators suffer from inaccuracies…
Vision-Based Uncertainty-Aware Motion Planning based on Probabilistic Semantic Segmentation
Ralf Römer, Armin Lederer, Samuel Tesfazgi +1
For safe operation, a robot must be able to avoid collisions in uncertain environments. Existing approaches for motion planning under uncertainties often assume parametric obstacle…
Dext-Gen: Dexterous Grasping in Sparse Reward Environments with Full Orientation Control
Martin Schuck, Jan Brüdigam, Alexandre Capone +2
Reinforcement learning is a promising method for robotic grasping as it can learn effective reaching and grasping policies in difficult scenarios. However, achieving human-like man…
Linear-Time Contact and Friction Dynamics in Maximal Coordinates using Variational Integrators
Jan Brüdigam, Jana Janeva, Stefan Sosnowski +1
Simulation of contact and friction dynamics is an important basis for control- and learning-based algorithms. However, the numerical difficulties of contact interactions pose a cha…
Distributed Event- and Self-Triggered Coverage Control with Speed Constrained Unicycle Robots
Yuni Zhou, Lingxuan Kong, Stefan Sosnowski +2
Voronoi coverage control is a particular problem of importance in the area of multi-robot systems, which considers a network of multiple autonomous robots, tasked with optimally co…
Gaussian Process-based Stochastic Model Predictive Control for Overtaking in Autonomous Racing
Tim Brüdigam, Alexandre Capone, Sandra Hirche +2
A fundamental aspect of racing is overtaking other race cars. Whereas previous research on autonomous racing has majorly focused on lap-time optimization, here, we propose a method…
Distributed Bayesian Online Learning for Cooperative Manipulation
Pablo Budde gen. Dohmann, Armin Lederer, Marcel Dißemond +1
For tasks where the dynamics of multiple agents are physically coupled, e.g., in cooperative manipulation, the coordination between the individual agents becomes crucial, which req…
Fully distributed cooperation for networked uncertain mobile manipulators
Yi Ren, Sandra Hirche
This paper investigates a fully distributed cooperation scheme for networked mobile manipulators. To achieve cooperative task allocation in a distributed way, an adaptation-based e…
Inverse Optimal Control from Incomplete Trajectory Observations
Wanxin Jin, Dana Kulić, Shaoshuai Mou +1
This article develops a methodology that enables learning an objective function of an optimal control system from incomplete trajectory observations. The objective function is assu…
Object Handover Prediction using Gaussian Processes clustered with Trajectory Classification
Muriel Lang, Satoshi Endo, Oliver Dunkley +1
A robotic system which approximates the user intention and appropriate complimentary motion is critical for successful human-robot interaction. %While the existing wearable sensors…