Cover Image

Constrained Gaussian Process Motion Planning via Stein Variational Newton Inference

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Jiayun, Pompetzki, Kay, Le, An Thai, Tong, Haolei, Peters, Jan, Chalvatzaki, Georgia
Format:	Preprint
Published:	2025
Subjects:	Robotics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Hierarchical Policy Blending as Inference for Reactive Robot Control
by: Hansel, Kay, et al.
Published: (2022)

Global Tensor Motion Planning
by: Le, An T., et al.
Published: (2024)

The Role of Embodiment in Intuitive Whole-Body Teleoperation for Mobile Manipulation
by: Moyen, Sophia Bianchi, et al.
Published: (2025)

Stein Variational Ergodic Surface Coverage with SE(3) Constraints
by: Li, Jiayun, et al.
Published: (2026)

Adaptive Diffusion Constrained Sampling for Bimanual Robot Manipulation
by: Tong, Haolei, et al.
Published: (2025)

Evetac: An Event-based Optical Tactile Sensor for Robotic Manipulation
by: Funk, Niklas, et al.
Published: (2023)

Domain Randomization via Entropy Maximization
by: Tiboni, Gabriele, et al.
Published: (2023)

Constrained Stein Variational Gradient Descent for Robot Perception, Planning, and Identification
by: Tabor, Griffin, et al.
Published: (2025)

A Unifying Variational Framework for Gaussian Process Motion Planning
by: Cosier, Lucas, et al.
Published: (2023)

MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions from Demonstrations
by: Prasad, Vignesh, et al.
Published: (2024)

Constrained Stein Variational Trajectory Optimization
by: Power, Thomas, et al.
Published: (2023)

Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers
by: Göksu, Yasemin, et al.
Published: (2024)

Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models
by: Carvalho, Joao, et al.
Published: (2023)

Semantic-Geometric Task Representations for Bimanual Manipulation from Human Demonstrations to Robot Action Planning
by: Herbert, Franziska, et al.
Published: (2026)

Dual Online Stein Variational Inference for Control and Dynamics
by: Barcelos, Lucas, et al.
Published: (2021)

Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations
by: Urain, Julen, et al.
Published: (2024)

IMPACT: An Implicit Active-Set Augmented Lagrangian for Fast Contact-Implicit Trajectory Optimization
by: Li, Jiayun, et al.
Published: (2026)

Learning Any-View 6DoF Robotic Grasping in Cluttered Scenes via Neural Surface Rendering
by: Jauhri, Snehal, et al.
Published: (2023)

Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning
by: Krohn, Rickmer, et al.
Published: (2025)

Learning Multimodal Latent Dynamics for Human-Robot Interaction
by: Prasad, Vignesh, et al.
Published: (2023)

Morphologically Symmetric Reinforcement Learning for Ambidextrous Bimanual Manipulation
by: Li, Zechu, et al.
Published: (2025)

AssistDLO: Assistive Teleoperation for Deformable Linear Object Manipulation
by: Guler, Berk, et al.
Published: (2026)

UniFField: A Generalizable Unified Neural Feature Field for Visual, Semantic, and Spatial Uncertainties in Any Scene
by: Maurer, Christian, et al.
Published: (2025)

2HandedAfforder: Learning Precise Actionable Bimanual Affordances from Human Videos
by: Heidinger, Marvin, et al.
Published: (2025)

Gaussian Variational Inference with Non-Gaussian Factors for State Estimation: A UWB Localization Case Study
by: Stirling, Andrew, et al.
Published: (2025)

Discrete Variational Autoencoding via Policy Search
by: Drolet, Michael, et al.
Published: (2025)

Safe and Efficient Path Planning under Uncertainty via Deep Collision Probability Fields
by: Herrmann, Felix, et al.
Published: (2024)

Task-Aware Bimanual Affordance Prediction via VLM-Guided Semantic-Geometric Reasoning
by: Hahne, Fabian, et al.
Published: (2026)

Q-Guided Stein Variational Model Predictive Control via RL-informed Policy Prior
by: Cai, Shizhe, et al.
Published: (2025)

A Safety-Aware Shared Autonomy Framework with BarrierIK Using Control Barrier Functions
by: Guler, Berk, et al.
Published: (2026)

Model Tensor Planning
by: Le, An T., et al.
Published: (2025)

Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning
by: Kicki, Piotr, et al.
Published: (2024)

UniConFlow: A Unified Constrained Flow-Matching Framework for Certified Motion Planning
by: Yang, Zewen, et al.
Published: (2025)

Reward Redistribution via Gaussian Process Likelihood Estimation
by: Xiao, Minheng, et al.
Published: (2025)

Active-Perceptive Motion Generation for Mobile Manipulation
by: Jauhri, Snehal, et al.
Published: (2023)

BOMP: Bin-Optimized Motion Planning
by: Tam, Zachary, et al.
Published: (2024)

Multi-Embodiment Locomotion at Scale with extreme Embodiment Randomization
by: Bohlinger, Nico, et al.
Published: (2025)

Efficient Stochastic Optimal Control through Approximate Bayesian Input Inference
by: Watson, Joe, et al.
Published: (2021)

Structure-Preserving Gaussian Processes Via Discrete Euler-Lagrange Equations
by: Ewering, Jan-Hendrik, et al.
Published: (2026)

Cascaded Diffusion Models for Neural Motion Planning
by: Sharma, Mohit, et al.
Published: (2025)