Measure the Sim-to-Real Gap: Designing an Affordable Real-World Benchmark Platform for Reinforcement Learning in AIoT Systems

arXiv:2607.10309 · cs.AI · Submitted 2026-07-11 · Read on arXiv

cs.AI

Submitted: 2026-07-11

Updated: 2026-09-19

Comments: The code for this paper is available upon the request from the author

Code: https://github.com/RongpingZhou/real

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

Terminology

• Benchmark — 47× in this paper · explained in 2 episodes
• Reinforcement Learning — 40× in this paper · explained in 4 episodes
• Human Normalized Score — 27× in this paper
• Sim-to-Real Gap — 19× in this paper · explained in 6 episodes
• Robustness — 17× in this paper · explained in 5 episodes
• Deep Reinforcement Learning — 7× in this paper · explained in 2 episodes
• Edge Devices — 7× in this paper · explained in 2 episodes
• Transferability — 5× in this paper · explained in 4 episodes
• Action Space — 4× in this paper · explained in 1 episode
• Adaptation — 3× in this paper · explained in 1 episode
• Arcade Learning Environment — 3× in this paper
• Autonomous Internet of Things — 3× in this paper
• Benchmarking — 3× in this paper · explained in 3 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Reinforcement Learning (RL) — 2× in this paper · explained in 25 episodes
• Reward Function — 2× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Energy Efficiency — 1× in this paper · explained in 3 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Physical Constraints — 1× in this paper · explained in 7 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• OpenAI Gym
• Gymnasium: A Standard Interface for Reinforcement Learning Environments
• Physical Atari: A Robust and Accessible Platform for Real-time Reinforcement Learning on Robots
• Continuous control with deep reinforcement learning
• Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
• Proximal Policy Optimization Algorithms

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