The First WARA Robotics Mobile Manipulation Challenge -- Lessons Learned
David C\'aceres Dom\'inguez, Marco Iannotta, Abhishek Kashyap, Shuo Sun, Yuxuan Yang, Christian Cella, Matteo Colombo, Martina Pelosi, Giuseppe F. Preziosa, Alessandra Tafuro, Isacco Zappa, Finn Busch, Yifei Dong, Alberta Longhini, Haofei Lu, Rafael I. Cabral Muchacho

TL;DR
This paper reports on the inaugural WARA Robotics Mobile Manipulation Challenge, highlighting diverse approaches to autonomous lab tasks, lessons learned, and future improvements to foster academia-industry collaboration in robotic manipulation.
Contribution
It introduces the first challenge focused on mobile manipulation in laboratory environments, showcasing innovative solutions and lessons for future industrial robotics applications.
Findings
Multiple approaches demonstrated effective navigation and manipulation in labs.
Lessons learned inform design improvements for future challenges.
The challenge fosters academia-industry collaboration in robotics.
Abstract
The first WARA Robotics Mobile Manipulation Challenge, held in December 2024 at ABB Corporate Research in V\"aster{\aa}s, Sweden, addressed the automation of task-intensive and repetitive manual labor in laboratory environments - specifically the transport and cleaning of glassware. Designed in collaboration with AstraZeneca, the challenge invited academic teams to develop autonomous robotic systems capable of navigating human-populated lab spaces and performing complex manipulation tasks, such as loading items into industrial dishwashers. This paper presents an overview of the challenge setup, its industrial motivation, and the four distinct approaches proposed by the participating teams. We summarize lessons learned from this edition and propose improvements in design to enable a more effective second iteration to take place in 2025. The initiative bridges an important gap in…
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Taxonomy
TopicsRobot Manipulation and Learning · Robotic Path Planning Algorithms · Digital Transformation in Industry
