This content has no audio.
Researchers from Finland, Switzerland, Spain and Romania gathered at Tampere University in Finland for a workshop within the Robosat project focused on localizing autonomous machines.
Workshop participants discussed and demonstrated new technological solutions to improve the localization of autonomous machines, especially those operating in unconstrained and difficult environments such as forests and mountainous areas.
The Robosat project aims to transform the way autonomous robots move in the field by integrating multi-sensor and multi-GIS data. During the workshop in Tampere, our partners from Tampere University (Finland) ETH Zurich (Switzerland), University of Valencia (Spain), and CITST (Romania) discussed strategies for sharing data, identifying relevant GIS and GNSS datasets, and leveraging AI for autonomous labeling of large-scale data.
Key topics include integrating multi-sensor and multi-GIS data to improve positioning accuracy, planning a pilot test using ETH's ANYmal robot and TAU's new I/Q GNSS grabber device, and discussing AI-driven data labeling methods for large datasets collected during field trials.
The project team at Tampere University has Elena Simona Rohan and Jari Nurmi as supervisors and Ph.D. Students Elizaveta Pervisheva and Muhammad Safi.
RoboSat efforts support applications in robotics, environmental monitoring, and industrial automation. By combining expertise from across Europe, Robosat intends to pave the way for smarter, safer and more efficient autonomous systems.
It also aims to provide new open access rich datasets to the research community. The first dataset enabling multimodal classification studies has already been published on Zenodo as a collaboration between the University of Tampere and the CITST team.
robosat project
Autonomous navigation of wild robots using satellite-based 3D geographic information (ROBOSAT) aims to provide a scalable MultiGIS high-quality data collection platform through the use of quadrupedal robots that can autonomously perform long-range missions in harsh environments such as the Alps and Finnish forests.
The consortium organization consists of three universities and one small business.
- University of Tampere, Finland. Expertise: GNSS, wireless positioning, sensing, communications, RF fingerprinting and interference mitigation. Coordinator: Elena Simona Rohan
- Swiss Federal Institute of Technology. Areas of expertise: automation, mapping, control theory, research on legged robots. PI: marco hitter
- University of Valencia, Spain. Expertise: Computer Science, Database Management, Machine Learning. PI: Joaquín Torres Sospedra
- CITST, Romania. Expertise: Machine Learning/Artificial Intelligence, Robotics, Exploitation. PI: Irina Mocanu.
