机器人ICLR 20252025
SimplerEnv: Evaluating Real-World Robot Policies in Simulation
Xuanlin Li, Kyle Hsu, Jiayuan Gu, Karl Pertsch, Chelsea FinnStanford University, UC Berkeley
摘要
We present SimplerEnv, a simulation-based evaluation framework for assessing real-world robot policy performance. SimplerEnv provides photorealistic environments with accurate physics to benchmark manipulation policies, revealing critical gaps between simulated and real-world performance.
robot evaluationsimulation benchmarkpolicy assessmentphotorealisticmanipulation
技术细节
数据集
测试机器人
FR3WidowX-250
模型骨架
Evaluation Framework (multiple policy baselines)
编码器
ViT + Proprioceptive Encoders
解码器
Policy Decoders (RT-1, Octo, OpenVLA variants)