Control Your Robot: A Unified System for Robot Control and Policy Deployment

2025-09-28

AI Summary

Cross-platform robot control suffers from fragmented toolchains and inefficient deployment due to heterogeneity in hardware interfaces, data formats, and control paradigms. To address this, we propose RobUni—a modular, unified framework for robot control and policy deployment. RobUni standardizes end-to-end workflows, provides a unified hardware abstraction API, and incorporates a closed-loop simulation architecture enabling flexible device registration and dual-mode operation (teleoperation and trajectory playback). It tightly integrates multimodal perception, real-time inference, and closed-loop execution, ensuring seamless data acquisition-to-action generation. Evaluated on single- and dual-arm platforms, RobUni achieves sub-100 ms latency in data acquisition. Policies trained via imitation learning and vision-language-action modeling on collected data match human expert performance. This work significantly improves reproducibility, scalability, and cross-platform compatibility in robot learning.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Computer Vision: Vision for Robotics & Autonomous Driving

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search

Abstract

Cross-platform robot control remains difficult because hardware interfaces, data formats, and control paradigms vary widely, which fragments toolchains and slows deployment. To address this, we present Control Your Robot, a modular, general-purpose framework that unifies data collection and policy deployment across diverse platforms. The system reduces fragmentation through a standardized workflow with modular design, unified APIs, and a closed-loop architecture. It supports flexible robot registration, dual-mode control with teleoperation and trajectory playback, and seamless integration from multimodal data acquisition to inference. Experiments on single-arm and dual-arm systems show efficient, low-latency data collection and effective support for policy learning with imitation learning and vision-language-action models. Policies trained on data gathered by Control Your Robot match expert demonstrations closely, indicating that the framework enables scalable and reproducible robot learning across platforms.

Problem

• Unifying cross-platform robot control and policy deployment
• Reducing toolchain fragmentation through standardized modular workflow
• Enabling scalable robot learning with imitation and vision-language models

Innovation

• Modular framework unifying robot control and deployment
• Standardized workflow with unified APIs and closed-loop architecture
• Supports dual-mode control and multimodal data integration