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Lessons learned from the RAICAM doctoral network research sprints and field demonstrations

Kenan, Alperen ; Sadeghi Kordkheili, Sahar; Garcia Cardenas, Juan Jose; Guidali, Valentina; Melone, Alessandro; Tian, Changda; Dincer, Enes Ulas 1; Li, Haichuan; Raei, Hamidreza; Arachchige, Sasanka Kuruppu; Tang, Yifeng; Tapus, Adriana; Ollero, Anibal; Gonzalez-Morgado, Antonio; Ajudani, Arash; Arrue, Begoña C.; Piazza, Cristina; Papageorgiou, Dimitrios; Neumann, Gerhard; ... mehr

Abstract:

Doctoral Networks (DNs) aim to address systemic challenges in doctoral education, such as fostering interdisciplinarity, enabling international and intersectoral collaboration, enhancing employability, and promoting responsible innovation. While cohort-based training helps mitigate student isolation through workshops and summer schools, traditional DNs often struggle to fully realize their collaborative potential, often relying on predefined supervisor relationships or the initiative of individual researchers. In contrast, the Marie Skłodowska-Curie Actions (MSCA) Robotics and AI for Critical Asset Monitoring (RAICAM) DN was designed to maximize doctoral candidate (DC) collaboration and networking through a cohort-wide research challenge, requiring them to balance independent research with contributions to a shared, mission-driven objective. This study examines how structured training, including digital communities, application-focused research sprints, training schools, a robotics hackathon and a final demonstration enhances system integration and collaboration within the network. DCs located across seven European countries worked in virtual teams, refining systems through structured workflows, weekly meetings, and shared workspaces before training schools. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000194162
Veröffentlicht am 12.06.2026
Originalveröffentlichung
DOI: 10.1016/j.robot.2026.105523
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 09.2026
Sprache Englisch
Identifikator ISSN: 0921-8890
KITopen-ID: 1000194162
Erschienen in Robotics and Autonomous Systems
Verlag Elsevier
Band 203
Seiten Art.-Nr.: 105523
Vorab online veröffentlicht am 20.05.2026
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