Image de couverture de livre

The Unreasonable Effectiveness of Discrete-Time Gaussian Process Mixtures for Robot Policy Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	von Hartz, Jan Ole, Röfer, Adrian, Boedecker, Joschka, Valada, Abhinav
Format:	Preprint
Publié:	2025
Sujets:	Robotics Artificial Intelligence Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

MSG: Multi-Stream Generative Policies for Sample-Efficient Robotic Manipulation
par: von Hartz, Jan Ole, et autres
Publié: (2025)

The Art of Imitation: Learning Long-Horizon Manipulation Tasks from Few Demonstrations
par: von Hartz, Jan Ole, et autres
Publié: (2024)

The Neural Compass: Probabilistic Relative Feature Fields for Robotic Search
par: Somaschini, Gabriele, et autres
Publié: (2026)

Spectral Alignment in Forward-Backward Representations via Temporal Abstraction
par: Azad, Seyed Mahdi B., et autres
Publié: (2026)

Whole-Body Teleoperation for Mobile Manipulation at Zero Added Cost
par: Honerkamp, Daniel, et autres
Publié: (2024)

Information-Theoretic Policy Pre-Training with Empowerment
par: Schneider, Moritz, et autres
Publié: (2025)

Online Estimation and Manipulation of Articulated Objects
par: Buchanan, Russell, et autres
Publié: (2026)

Context-Conditional Navigation with a Learning-Based Terrain- and Robot-Aware Dynamics Model
par: Guttikonda, Suresh, et autres
Publié: (2023)

Robotic Task Ambiguity Resolution via Natural Language Interaction
par: Chisari, Eugenio, et autres
Publié: (2025)

Designing for Difference: How Human Characteristics Shape Perceptions of Collaborative Robots
par: Livanec, Sabrina, et autres
Publié: (2025)

Discrete Variational Autoencoding via Policy Search
par: Drolet, Michael, et autres
Publié: (2025)

Motion Forecasting via Model-Based Risk Minimization
par: Distelzweig, Aron, et autres
Publié: (2024)

Bayesian Optimization for Sample-Efficient Policy Improvement in Robotic Manipulation
par: Röfer, Adrian, et autres
Publié: (2024)

Hyperspectral Adapter for Semantic Segmentation with Vision Foundation Models
par: Hurtado, Juana Valeria, et autres
Publié: (2025)

Adaptive Gaussian Mixture Models-based Anomaly Detection for under-constrained Cable-Driven Parallel Robots
par: Garrido, Julio, et autres
Publié: (2025)

SparTa: Sparse Graphical Task Models from a Handful of Demonstrations
par: Röfer, Adrian, et autres
Publié: (2026)

Unsupervised Learning of Effective Actions in Robotics
par: Zaric, Marko, et autres
Publié: (2024)

Latent Linear Quadratic Regulator for Robotic Control Tasks
par: Zhang, Yuan, et autres
Publié: (2024)

Revisiting Safe Exploration in Safe Reinforcement learning
par: Eckel, David, et autres
Publié: (2024)

Evolutionary Policy Optimization
par: Wang, Jianren, et autres
Publié: (2025)

Preference-Based Long-Horizon Robotic Stacking with Multimodal Large Language Models
par: Yu, Wanming, et autres
Publié: (2025)

Hierarchical Open-Vocabulary 3D Scene Graphs for Language-Grounded Robot Navigation
par: Werby, Abdelrhman, et autres
Publié: (2024)

Variational Distillation of Diffusion Policies into Mixture of Experts
par: Zhou, Hongyi, et autres
Publié: (2024)

Robot Policy Learning with Temporal Optimal Transport Reward
par: Fu, Yuwei, et autres
Publié: (2024)

Body Transformer: Leveraging Robot Embodiment for Policy Learning
par: Sferrazza, Carmelo, et autres
Publié: (2024)

ForecastOcc: Vision-based Semantic Occupancy Forecasting
par: Mohan, Riya, et autres
Publié: (2026)

RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
par: Xu, Charles, et autres
Publié: (2024)

RobotKeyframing: Learning Locomotion with High-Level Objectives via Mixture of Dense and Sparse Rewards
par: Zargarbashi, Fatemeh, et autres
Publié: (2024)

Open-Set LiDAR Panoptic Segmentation Guided by Uncertainty-Aware Learning
par: Mohan, Rohit, et autres
Publié: (2025)

Neural Fields in Robotics: A Survey
par: Irshad, Muhammad Zubair, et autres
Publié: (2024)

Linear Mixture Distributionally Robust Markov Decision Processes
par: Liu, Zhishuai, et autres
Publié: (2025)

Robot Policy Transfer with Online Demonstrations: An Active Reinforcement Learning Approach
par: Hou, Muhan, et autres
Publié: (2025)

Reinforcement Learning Within the Classical Robotics Stack: A Case Study in Robot Soccer
par: Labiosa, Adam, et autres
Publié: (2024)

QMP: Q-switch Mixture of Policies for Multi-Task Behavior Sharing
par: Zhang, Grace, et autres
Publié: (2023)

Learning and Blending Robot Hugging Behaviors in Time and Space
par: Drolet, Michael, et autres
Publié: (2022)

Tool-as-Interface: Learning Robot Policies from Observing Human Tool Use
par: Chen, Haonan, et autres
Publié: (2025)

Confidence-Controlled Exploration: Efficient Sparse-Reward Policy Learning for Robot Navigation
par: Patel, Bhrij, et autres
Publié: (2023)

DiffClone: Enhanced Behaviour Cloning in Robotics with Diffusion-Driven Policy Learning
par: Mani, Sabariswaran, et autres
Publié: (2024)

Automating the Refinement of Reinforcement Learning Specifications
par: Ambadkar, Tanmay, et autres
Publié: (2025)

Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planning
par: Liang, Jinhao, et autres
Publié: (2025)