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To address this, robotic systems can be designed as self-adaptive systems capable of adapting their task execution and software architecture at runtime based on their context. This paper introduces ROSA, a novel knowledge-based framework for RObot Self-Adaptation, which enables task-and-architecture co-adaptation (TACA) in robotic systems. ROSA achieves this by providing a knowledge model that captures all application-specific knowledge required for adaptation and by reasoning over this knowledge at runtime to determine when and how adaptation should occur. In addition to a conceptual framework, this work provides an open-source ROS 2-based reference implementation of ROSA and evaluates its feasibility and performance in an underwater robotics application. Experimental results highlight ROSA\u2019s advantages in reusability and development effort for designing self-adaptive robotic systems.<\/jats:p>","DOI":"10.3389\/frobt.2025.1531743","type":"journal-article","created":{"date-parts":[[2025,5,20]],"date-time":"2025-05-20T09:46:22Z","timestamp":1747734382000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["ROSA: a knowledge-based solution for robot self-adaptation"],"prefix":"10.3389","volume":"12","author":[{"given":"Gustavo","family":"Rezende Silva","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juliane","family":"P\u00e4\u00dfler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S. 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