InsertAnything: Generalizable Contact-Rich Precision Insertion from Simulation to Reality

arXiv:2609.24511 · cs.RO · Submitted 2026-09-21 · Read on arXiv

cs.RO

Submitted: 2026-09-21

Updated: 2026-09-21

Project page: https://mzhsoul.github.io/InsertAnything

Terminology

• Alignment — 42× in this paper · explained in 1 episode
• Reinforcement Learning — 18× in this paper · explained in 4 episodes
• Generalization — 15× in this paper · explained in 13 episodes
• Ablation — 12× in this paper · explained in 1 episode
• Fine-Tuning — 11× in this paper · explained in 5 episodes
• Benchmark — 10× in this paper · explained in 2 episodes
• Actor — 6× in this paper · explained in 3 episodes
• Calibration — 6× in this paper · explained in 7 episodes
• Human-in-the-Loop — 6× in this paper · explained in 3 episodes
• AUC — 4× in this paper · explained in 2 episodes
• International Conference on Robotics and Automation — 4× in this paper
• Robustness — 3× in this paper · explained in 5 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Angular Error — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Decoupling — 2× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 2× in this paper · explained in 2 episodes
• Sim-to-Real Transfer — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Action Chunking — 1× in this paper · explained in 1 episode
• Action Primitives — 1× in this paper · explained in 1 episode
• Action Space — 1× in this paper · explained in 1 episode
• Closed-Loop System — 1× in this paper · explained in 4 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Reward Hacking — 1× in this paper · explained in 8 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Sim-to-Real Gap — 1× in this paper · explained in 6 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Factory: Fast Contact for Robotic Assembly
• IndustReal: Transferring Contact-Rich Assembly Tasks from Simulation to Reality
• ReTac-ACT: A State-Gated Vision-Tactile Fusion Transformer for Precision Assembly
• ManipulationNet: An Infrastructure for Benchmarking Real-World Robot Manipulation with Physical Skill Challenges and Embodied Multimodal Reasoning
• Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning
• Proximal Policy Optimization Algorithms
• Concrete Problems in AI Safety

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