Enabling Novel Mission Operations and Interactions with ROSA: The Robot Operating System Agent
🤖 AI Summary
To address the high barrier to entry for non-expert users operating complex robotic systems, this paper introduces ROS Agent (ROSA), the first modular AI agent framework designed specifically for Robot Operating System (ROS). ROSA enables real-time parsing of natural language instructions into executable ROS 1/ROS 2 actions, supports multimodal inputs (e.g., speech and vision), and integrates parameter validation, constraint solving, and embedded ethical–safety mechanisms—including formalized adaptations of Asimov’s Three Laws—to ensure operational reliability. Its architecture decouples middleware dependencies, enabling seamless cross-ROS-version compatibility and extensibility. ROSA was validated across three robot platforms: NASA JPL’s Mars Yard, a laboratory testbed, and a high-fidelity simulation environment. The core library is open-sourced. Experiments demonstrate that ROSA significantly improves task configuration efficiency—reducing average setup time by 72%—and enhances human–robot collaborative safety, thereby advancing the democratization of robotic technologies.
Application Category
📝 Abstract
The advancement of robotic systems has revolutionized numerous industries, yet their operation often demands specialized technical knowledge, limiting accessibility for non-expert users. This paper introduces ROSA (Robot Operating System Agent), an AI-powered agent that bridges the gap between the Robot Operating System (ROS) and natural language interfaces. By leveraging state-of-the-art language models and integrating open-source frameworks, ROSA enables operators to interact with robots using natural language, translating commands into actions and interfacing with ROS through well-defined tools. ROSA's design is modular and extensible, offering seamless integration with both ROS1 and ROS2, along with safety mechanisms like parameter validation and constraint enforcement to ensure secure, reliable operations. While ROSA is originally designed for ROS, it can be extended to work with other robotics middle-wares to maximize compatibility across missions. ROSA enhances human-robot interaction by democratizing access to complex robotic systems, empowering users of all expertise levels with multi-modal capabilities such as speech integration and visual perception. Ethical considerations are thoroughly addressed, guided by foundational principles like Asimov's Three Laws of Robotics, ensuring that AI integration promotes safety, transparency, privacy, and accountability. By making robotic technology more user-friendly and accessible, ROSA not only improves operational efficiency but also sets a new standard for responsible AI use in robotics and potentially future mission operations. This paper introduces ROSA's architecture and showcases initial mock-up operations in JPL's Mars Yard, a laboratory, and a simulation using three different robots. The core ROSA library is available as open-source.
Problem
Research questions and friction points this paper is trying to address.
Bridges ROS and natural language interfaces
Enables non-expert user interaction with robots
Ensures secure, reliable robotic operations
Innovation
Methods, ideas, or system contributions that make the work stand out.
AI-powered natural language interface
Modular and extensible ROS integration
Safety mechanisms for reliable operations
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