Learning Geometry-Aware Virtual Fixtures From Sparse Demonstrations

arXiv:2609.32958 · cs.RO · Submitted 2026-09-26 · Read on arXiv

cs.RO

Submitted: 2026-09-26

Updated: 2026-09-26

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 4× in this paper · explained in 1 episode
• Linear Quadratic Tracking — 4× in this paper
• Adaptation — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Gaussian Mixture Regression — 2× in this paper
• Generalization — 2× in this paper · explained in 13 episodes
• Gaussian Mixture Model — 1× in this paper
• Gaussian Mixture Model (GMM) — 1× in this paper · explained in 2 episodes
• Gaussian Processes (GPs) — 1× in this paper · explained in 2 episodes
• IEEE International Conference on Robotics and Automation — 1× in this paper
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• A Unified Framework for Probabilistic Dynamic-, Trajectory- and Vision-based Virtual Fixtures
• Passive Variable Impedance For Shared Control

Related papers

• FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
• MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
• RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
• ARC: A Reasoning Recipe for Robot Foundation Models
• HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
• APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies