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Enabling Novel Mission Operations and Interactions with ROSA: The Robot Operating System Agent

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arxiv 2410.06472 v2 pith:DVOMIJBU submitted 2024-10-09 cs.RO cs.AIcs.HC

classification cs.ROcs.AIcs.HC
keywords rosaoperationsagentintegrationlanguageoperatingrobotrobotic
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Governed Capability Evolution: Lifecycle-Time Compatibility Checking and Rollback for AI-Component-Based Systems, with Embodied Agents as Case Study

    cs.RO 2026-04 unverdicted novelty 7.0 of 10

    A governed upgrade framework with interface, policy, behavioral, and recovery checks keeps unsafe activations at zero across multi-round AI capability upgrades on a PyBullet/ROS 2 manipulation testbed while retaining ...

  2. AEROS: A Single-Agent Operating Architecture with Embodied Capability Modules

    cs.RO 2026-04 unverdicted novelty 6.0 of 10

    Robots are modeled as single persistent agents extended by installable Embodied Capability Modules under policy-enforced runtime, yielding 100% task success in simulation versus lower baseline rates.

  3. ROS Help Desk: GenAI Powered, User-Centric Framework for ROS Error Diagnosis and Debugging

    cs.RO 2025-07 conditional novelty 5.0 of 10

    ROS Help Desk combines log monitoring, sensor anomaly checks, and a chat agent with retrieval to detect and explain robot errors proactively.

  4. Taking Flight with Dialogue: Enabling Natural Language Control for PX4-based Drone Agent

    cs.RO 2025-06 conditional novelty 5.0 of 10

    An open-source ROS2/PX4 framework using locally hosted LLMs and VLMs enables natural language drone commands, with the best simulated mission success rate at 40%.

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