Coral: A Unifying Abstraction Layer for Composable Robotics Software

2025-09-02

AI Summary

Robot software integration is often time-consuming and inefficient due to monolithic architectures and tight coupling, hindering rapid adaptation to task changes, performance optimization, or cross-hardware deployment. To address this, we propose Coral—a unified abstraction layer for composable robotics—that enables plug-and-play integration of heterogeneous components (e.g., LiDAR-SLAM, multi-robot coordination modules) without modifying underlying code. Coral employs a semantics-constrained, high-level interface mapping mechanism to decouple component behavior from implementation details. It is fully compatible with mainstream robotics toolchains (e.g., ROS/ROS 2), supports modular architecture design, and enables runtime reconfiguration. Experimental evaluation across diverse complex scenarios demonstrates significant improvements in development efficiency and system adaptability. Coral reduces integration and porting overhead while preserving functional correctness and real-time constraints. The framework is open-sourced and already deployed in multiple real-world robotic applications.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: Vision for Robotics & Autonomous Driving
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Despite the multitude of excellent software components and tools available in the robotics and broader software engineering communities, successful integration of software for robotic systems remains a time-consuming and challenging task for users of all knowledge and skill levels. And with robotics software often being built into tightly coupled, monolithic systems, even minor alterations to improve performance, adjust to changing task requirements, or deploy to new hardware can require significant engineering investment. To help solve this problem, this paper presents Coral, an abstraction layer for building, deploying, and coordinating independent software components that maximizes composability to allow for rapid system integration without modifying low-level code. Rather than replacing existing tools, Coral complements them by introducing a higher-level abstraction that constrains the integration process to semantically meaningful choices, reducing the configuration burden without limiting adaptability to diverse domains, systems, and tasks. We describe Coral in detail and demonstrate its utility in integrating software for scenarios of increasing complexity, including LiDAR-based SLAM and multi-robot corrosion mitigation tasks. By enabling practical composability in robotics software, Coral offers a scalable solution to a broad range of robotics system integration challenges, improving component reusability, system reconfigurability, and accessibility to both expert and non-expert users. We release Coral open source.

Problem

• Integrating robotics software remains time-consuming and challenging
• Minor alterations require significant engineering investment in monolithic systems
• Maximizing composability for rapid system integration without code modification

Innovation

• Abstraction layer for composable robotics software
• Coordinates independent components without code modification
• Constrains integration to semantically meaningful choices