WORKSHOP with sister project 

On November 30, 2023, FEROX run an online workshop with its sister projects DIGIFOREST, FLEXIROBOTS, AUTOASSESS and ICAERUS.


This workshop has the objective of sharing knowledge and experiences of Horizon Europe projects that share the common theme of drones & AI for real-world applications. 


The FEROX project aims to support workers with collecting wild berries and mushrooms in wild and remote areas of Nordic countries. The project solution exploits the latest advances in artificial intelligence (AI), data and drone technologies. The need for a solution that improves the human experience during forest foraging is substantial. As wild berries and mushrooms grow in forests, the access to these products is very challenging. Commercial picking work is performed manually and is generally conducted by foreign workers. It requires physical capabilities and patience in varying weather conditions during the summer season. In addition, as the workers are from foreign countries with very little knowledge of the work locations and the native language, some of them may suffer from anxieties of being injured or lost in the forests. Moreover, the optimum locations for the workers to pick the products are uncertain, which exerts added pressure on the workers to locate themselves optimally as their pay relies entirely on the amount of berries and mushrooms they collect daily. These and many other reasons have motivated the consortium to introduce the FEROX project.


The DIGI-FOREST project aims to develop the technology needed to achieve sustainable digital forestry. The following four scientific ambitions form the basis of our project: (1) mobile robotic navigation (multi-sensor motion estimation, 3D mission planning) (2) data-driven semantic mapping (3) Data presentation to human supervisors to make better informed decisions (4) deployment planning of a mobile robot harvester to selectively intervene in an environmental manner. Mobile robots will act as the core enabler for the proposed next-generation forestry: they will be tasked with data collection for map building, and in turn decision support, as well as navigating the harvester to cut individual trees. Safely deploying a heterogeneous team of robots in an unstructured forest still poses a major challenge.


The FLEXIGROBOTS project aims to enable Agricultural robotics solutions by integrating a variety of robots for a variety of monitoring and targeted intervention tasks, to increase farm productivity, efficiency and sustainability through support of automated precision farming operations. Despite the rising farmer investment in farm/agricultural robots, most deployable robotic systems are meant to automate only specific tasks. The wide variety of tasks that need to be fulfilled in a single precision agriculture operation or mission makes it extremely unprofitable to address its automation with task-specific robots. These challenges result in a lack of flexibility of current heterogeneous multi-robot systems that poses low returns on investment and high risks for farmers. In order to become cost-effective, heterogeneous multi-robot systems needs to become more flexible by employing more versatile (e.g. multi-task) robots which collaborate to accomplish complex missions; ensuring scalable human oversight and intervention through adaptive mission control mechanisms (e.g. without information overload /overwhelming effort from the farmer); allowing the farmer to profit from robotics operational data. FlexiGroBots proposes a Platform for developing heterogeneous multi-robot systems and applications which allows for i) more versatility by using the same robots for different observation and intervention tasks, in different missions, throughout the crop life cycle, ii) more cooperation between heterogeneous (ground and aerial) robots to accomplish more complex missions; iii) more valuable data to generate accurate insights into the fields, crops and robotics operations by combining data from IoT sensors, satellites and data collected by the robots; iv) more autonomy for real-time adaptation of mission plans as well as robot behaviour at the crop level, given operational conditions and real-time insights; v) more precision to carry out specific tasks in a very localised way, gaining accuracy and lowering costs.


The AUTOASSESS project deals with critical infrastructure structural surveying and aims to develop an autonomous robotic system-of-systems to remove humans, working in confined spaces from harm’s way, while demonstrating beyond human capabilities in terms of accuracy and repeatability of vessel inspection. AUTOASSESS tries to reach this goal by combining and integrating the latest developments in collision-tolerant UAS, multi-modal Simultaneous Localization and Mapping, path planning, autonomous drone racing, aerial manipulation, miniaturised NDT sensors and Machine Learning-based defect identification it is possible to deploy drones in these tight spaces for inspection purposes. 


The ICAERUS project aims to explore the multi-purpose application potential of drones in agricultural production, forestry and rural communities through five specific drone applications. The selected drone applications represent the most important sectoral and societal uses of drones in Europe and cover multiple applications that are interconnected within Europe's complex rural landscape. The project will identify the associated risks and added values and provide a more complete and interconnected account of the potential and impact of drones as multi-purpose vehicles. ICAERUS will further develop existing software technology, platform components and knowledge about drones either as positioning systems for visual observation and recording or as instruments for spraying and delivering goods.

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