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arXiv · 2509.08522

RoboMatch: A Unified Mobile-Manipulation Teleoperation Platform with Auto-Matching Network Architecture for Long-Horizon Tasks

Hanyu Liu·Yunsheng Ma·Jiaxin Huang·Keqiang Ren·Jiayi Wen·Yilin Zheng·Haoru Luan·Baishu Wan·Pan Li·Jiejun Hou·Zhihua Wang·Zhigong Song
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Abstract

This paper presents RoboMatch, a novel unified teleoperation platform for mobile manipulation with an auto-matching network architecture, designed to tackle long-horizon tasks in dynamic environments. Our system enhances teleoperation performance, data collection efficiency, task accuracy, and operational stability. The core of RoboMatch is a cockpit-style control interface that enables synchronous operation of the mobile base and dual arms, significantly improving control precision and data collection. Moreover, we introduce the Proprioceptive-Visual Enhanced Diffusion Policy (PVE-DP), which leverages Discrete Wavelet Transform (DWT) for multi-scale visual feature extraction and integrates high-precision IMUs at the end-effector to enrich proprioceptive feedback, substantially boosting fine manipulation performance. Furthermore, we propose an Auto-Matching Network (AMN) architecture that decomposes long-horizon tasks into logical sequences and dynamically assigns lightweight pre-trained models for distributed inference. Experimental results demonstrate that our approach improves data collection efficiency by over 20%, increases task success rates by 20-30% with PVE-DP, and enhances long-horizon inference performance by approximately 40% with AMN, offering a robust solution for complex manipulation tasks. Project website: https://robomatch.github.io

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Hanyu Liu, Yunsheng Ma, Jiaxin Huang, Keqiang Ren, Jiayi Wen, Yilin Zheng, Haoru Luan, Baishu Wan, Pan Li, Jiejun Hou, Zhihua Wang, Zhigong Song. 2025-09-10. RoboMatch: A Unified Mobile-Manipulation Teleoperation Platform with Auto-Matching Network Architecture for Long-Horizon Tasks. https://arxiv.org/abs/2509.08522

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