Periodic Reporting for period 1 - SYNERGISE (A novel integrated SYstem of Systems streNgthening tEchnical and logistical capacities to ensure better Response to emerGencies by synergIStically addrEssing FRs capability gaps)
Période du rapport: 2023-09-01 au 2024-11-30
This innovative toolkit is tailored for various emergency response agencies, including search and rescue teams, fire brigades, medical personnel, police, and civil protection organizations. NIT-CRES enhances collaboration, situational awareness, and efficiency through advanced tools and services. It enables FRs to explore disaster sites autonomously, monitor safety with real-time data on location and vitals, analyse threats, and coordinate efforts using a shared Common Operational Picture (COP). Designed with inclusiveness, privacy, and ethical considerations, the toolkit ensures compliance with operational standards and societal expectations.
The project includes extensive testing and validation activities to ensure practicality and user acceptance. By incorporating swarm robotics, localization systems, wearable health devices, augmented reality tools, and field communication systems into a unified framework, SYNERGISE provides FRs with enhanced capabilities for disaster management. A strong focus on human-machine teaming ensures seamless collaboration between responders and their tools.
SYNERGISE not only advances technological innovation but also prioritizes societal values by addressing ethical, legal, and privacy concerns. Its solutions are designed to be inclusive, sustainable, and trusted by users and stakeholders. The project’s holistic approach improves situational awareness, speeds up response times, and strengthens cross-border cooperation, contributing to a more resilient and safer society.
In summary, SYNERGISE delivers a transformative toolkit that empowers first responders to handle complex incidents effectively, enhances disaster resilience, and sets new standards for emergency management. By integrating advanced technology with societal responsibility, the project ensures a safer future for communities across Europe.
Robotics advancements included enhancing the ANYmal robot for precise end-effector control on rough terrain and integrating cameras and sensors into the SNAKE robot for navigating in confined spaces. Improvements in robotic perception enabled bandwidth-efficient map sharing, collaborative exploration with ground and aerial robots, and intuitive interfaces for robotic arm control. Real-time communication pipelines streamlined human-machine interaction.
Wearable and localization technologies were significantly refined, incorporating advanced features such as step detection, magnetic calibration, and sensors for monitoring vitals and detecting gas. These enhancements were seamlessly integrated into first responder equipment, with data collected during training and testing exercises providing valuable insights for further development.
Testing and validation activities played a critical role in advancing SYNERGISE technologies. These efforts encompassed 10 collaborative lab tests, a technical workshop, and the first field test, where the project's communication tools and network systems were evaluated alongside wearables and localisation devices. By adopting this comprehensive and hands-on approach, SYNERGISE ensured that its technologies were rigorously assessed under realistic conditions, leading to improved performance and reliability.
In parallel, communication and dissemination activities boosted the project's visibility. Through a public website, active social media engagement, and participation in over 39 key events, SYNERGISE reached a wide audience and strengthened its network. At every stage, ethical compliance and effective project coordination ensured the technologies were developed in alignment with user needs and societal expectations.
This first reporting period has built a strong foundation for advancing SYNERGISE technologies and improving disaster response capabilities.
The project also integrated the first prototypes of the SNAKE robot and the UAV (RMF-OWL) with ANYmal, showcasing the potential for collaborative multi-robot systems. For OWL, key developments include a novel method for bandwidth-efficient volumetric map sharing between legged and flying robots, semantic scene graph representations to enable more efficient path planning for faster search and rescue missions, and multi-modal localization and mapping capabilities to ensure resilient navigation in GNSS-denied and perceptually degraded environments.