AI summaryⓘ
The authors created XPolicyLab, a system that makes it easier to test and use different robot control programs (policies) with various robot simulators or real robots. Normally, connecting many policies to many environments requires many separate setups, but XPolicyLab simplifies this by using a common language and interface that both sides understand. This reduces the work needed to integrate new policies or environments from hours to minutes. The system keeps the unique parts of each policy separate, so environments and policies can run independently, even on different computers. Their tool supports many existing policies and works across both simulated and real robots, helping researchers compare and deploy robot behaviors more easily.
robot policypolicy evaluationrobot simulationadapter interfacepolicy inferencerobot deploymenttrajectory schemaclient/server architecturerobot controlreproducibility
Authors
XPolicyLab Community, Tianxing Chen, Yue Chen, Tian Nian, Zijian Cai, Guangyu Chen, Wenwei Lin, Qiwei Liang, Peicheng Xiang, Kailun Su, Zixuan Li, Junyuan Tang, Yan Qin, Qiangyu Chen, Shaolong Zhu, Xiang Li, Jiahao Zhang, Weijie Wan, Baijun Chen, Honghao Su, Kehe Ye, Shujia Liu, Kaixuan Wang, Haotian Liang, Yunze Liu, Mingleyang Li, Yuran Wang, Boyu Chen, Hongzhe Bi, Shuhe Huang, Hengkai Tan, Jisong Cai, Yao Mu, Jun Guo, Xiaofeng Wang, Zheng Zhu, Weijie Ke, Hengtao Li, Yuhang Tang, Xiaofan Li, Ganlin Yang, Zhangzheng Tu, Shuai Yang, Wenxuan Song, Pengxiang Ding, Kaidong Zhang, Yu Sun, Junliang Guo, Tong Zhang, Yixing Chen, Rongxu Cui, Zongzheng Zhang, Haoxiang Ma, Junhao Cai, Haoyu Zhang, Senqiao Yang, Jinhui Ye, Pengguang Chen, Shu Liu, Xiu Su, Wenhan Fang, Wenhao Li, Yichao Cao, Chengyao Wang, Qiang Chen, Ping Luo, Wenbo Ding
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/.