CORAL: A Unifying Abstraction Layer for Compositional Robotics Software

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 compositionality 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 configuration complexity 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 emphasizing practical compositionality 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 source1.