WorldEval: World Model as Real-World Robot Policies Evaluator

• URL: http://arxiv.org/abs/2505.19017v1
• Date: Sun, 25 May 2025 07:41:39 GMT
• Title: WorldEval: World Model as Real-World Robot Policies Evaluator
• Authors: Yaxuan Li, Yichen Zhu, Junjie Wen, Chaomin Shen, Yi Xu,
• Abstract summary: A key challenge is generating accurate policy videos from world models that faithfully reflect the robot actions.<n>We propose Policy2Vec, a simple yet effective approach to turn a video generation model into a world simulator that follows latent action to generate the robot video.<n>We then introduce WorldEval, an automated pipeline designed to evaluate real-world robot policies entirely online.
• Score: 13.899692171641066
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The field of robotics has made significant strides toward developing generalist robot manipulation policies. However, evaluating these policies in real-world scenarios remains time-consuming and challenging, particularly as the number of tasks scales and environmental conditions change. In this work, we demonstrate that world models can serve as a scalable, reproducible, and reliable proxy for real-world robot policy evaluation. A key challenge is generating accurate policy videos from world models that faithfully reflect the robot actions. We observe that directly inputting robot actions or using high-dimensional encoding methods often fails to generate action-following videos. To address this, we propose Policy2Vec, a simple yet effective approach to turn a video generation model into a world simulator that follows latent action to generate the robot video. We then introduce WorldEval, an automated pipeline designed to evaluate real-world robot policies entirely online. WorldEval effectively ranks various robot policies and individual checkpoints within a single policy, and functions as a safety detector to prevent dangerous actions by newly developed robot models. Through comprehensive paired evaluations of manipulation policies in real-world environments, we demonstrate a strong correlation between policy performance in WorldEval and real-world scenarios. Furthermore, our method significantly outperforms popular methods such as real-to-sim approach.

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