Precise, robust, and resilient localization in a remote environment

University of Turku

Mobile robots are set to take on a key role in improving many services, both in the civilian and industrial domains. In particular, UAVs and USVs are already important for environmental monitoring and sensing in both urban, rural and remote environments. In this project, research investigates the underlying technologies in robotics and AI. The development of a robust and resilient collaborative robotic framework holds the potential to establish a paradigm for multi-sensor integration and a more efficient monitoring system. This aims to empower mobile robots to undertake autonomous missions in complex and remote environments. Specifically, the focus is on using them for water monitoring and data collection to aid the development of Digital Twins for integrated water resource management.

This project aims to provide a precise, robust, and resilient localization for UAVs and USVs in remote environments. By leveraging the capability of LiDARs and other sensors, the project concentrates on designing and developing localization algorithms. These algorithms are intended to enhance GNSS, particularly under circumstances where the GNSS is unreliable or unavailable. The development of the localization algorithms will prioritize an end-to-end scheme that incorporates cross-modal fusion of various sensor types. The algorithm must be efficient and also maintain a lightweight architecture to facilitate seamless on-board integration within UAVs. This requirement is critical to ensure the feasibility of the algorithm’s deployment in real-world applications, where computational resources are often constrained. We will carry out missions in the Aura and Teno river environments.

We are looking for a doctoral researcher with a blend of independence and collaboration skills, motivated to work in a multinational and interdisciplinary team on projects involving multi-robot systems and embedded AI. An outstanding master’s degree in computer science, embedded students, robotics, mechatronics, or related fields, including master’s students who will complete their master’s degree in 2024 by the date set by the involved doctoral programme at UTU. Essential skills include proficiency in Python and C++ programming. Experience with machine learning technologies and practical experience with robots is seen as an advantage. Additionally, we value: – Experience with robotics sensors such as LiDARs, Cameras, and IMUs – Knowledge in LiDAR SLAM, odometry, and UAV Tracking – Familiarity with ROS for robotics programming -Hands-on practice of multi-modal sensor calibration Candidates should be prepared to engage in interdisciplinary research, demonstrating the ability to integrate methods and insights across different fields and leverage collaboration opportunities.

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Department of Computing, Faculty of Technology

Prof. Tomi Westerlund UTU

Prof. Jukka Heikkonen, UTU

Assoc. Prof. Wallace Moreira Bessa, UTU

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