XPolicyLab: A Unified Standard and Open Ecosystem for Robot Policy Evaluation and Deployment

2026-08-10

AI Summary

This work addresses the scalability challenge in robot policy evaluation and deployment, where fragmented models, datasets, and interfaces necessitate O(NM) independent integrations for N policies and M environments. To overcome this, the authors propose XPolicyLab—a unified, open framework that reduces integration complexity to O(N+M) by decoupling policy inference from environment execution via a client-server architecture. Central to this approach is a standardized schema for observations, actions, and trajectories, complemented by lightweight adapters that confine heterogeneity to the policy side. The framework enables consistent evaluation across both simulation and physical robots. In experiments, XPolicyLab integrated 42 diverse policies, reducing average per-policy integration time from five hours to thirty minutes, while maintaining compatibility with RoboTwin, RoboDojo, and real-world robotic platforms.

Abstract

Robot policy evaluation and deployment remain fragmented by model-specific software dependencies, data representations, and runtime interfaces, so that connecting N policies to M evaluation environments requires O(NM) separate integrations. We present XPolicyLab, a unified standard and open ecosystem that reduces this cost to O(N+M). XPolicyLab specifies common observation, action, and trajectory schemas together with a minimal adapter interface for observation updates, action prediction, batched execution, and episode reset, while a dependency-isolated client/server architecture separates policy inference from environment execution, so that each side retains its native software stack and may run locally or remotely. The ecosystem integrates 42 robot policies and standardizes their installation, debugging, serving, and evaluation workflows. Across these adapters, model-specific code varies by an order of magnitude while the environment-facing loop stays within a few lines of a fixed reference, confirming that the contract confines heterogeneity to the policy side. In a controlled study, conforming to the standard reduces the integration effort of a representative policy from over five hours to two hours, and packaged agent skills reduce it further to thirty minutes. The same adapters serve RoboTwin, RoboDojo simulation, and standardized real-robot evaluation through one interface. XPolicyLab is released as shared infrastructure for reproducible policy comparison and standardized deployment across simulation and physical platforms. Project website: https://xpolicylab.github.io/.

Problem

• robot policy
• evaluation
• deployment
• standardization
• integration

Innovation

• robot policy standardization
• adapter interface
• client-server architecture
• cross-platform deployment
• reproducible evaluation