Sustainability Aspects: Collaborative Robotics for Search & Rescue

Targeted Vertical: Life-saving environmental preservation

Partners:

• Institute of Communication & Computer Systems (ICCS): Use Case leader, Developer and Integrator
• National Center for Scientific Research ‘Demokritos’ (NCSRD) / ORGANISMOS TILEPIKOINONION TIS ELLADOS (ΟΤΕ): Testbed Providers
• ORGANISMOS TILEPIKOINONION TIS ELLADOS (ΟΤΕ): Telecom Operator
• INFOLYSiS: Developer & Integrator
• Elliniki Omada Diasosis Attikis (HRTA): End User

This use case focuses jointly on collaborative robotics search and rescue and early wildfire detection concepts. The exact trial site’s location will be determined during the preparation phase and the trials plan.

6G-VERSUS Greek Pilot – Collaborative robotics towards an early wildfire detection concept

Motivation and challenges:

Wildfires present significant challenges for search and rescue (SAR) operations because of their rapid evolution, hazardous conditions, limited visibility, difficult terrain, and the possibility of incomplete or degraded communication coverage. First responders may be exposed to smoke, extreme heat, rapidly changing fire fronts and areas that are difficult or unsafe to access. At the same time, effective SAR increasingly depends on timely situational awareness, early fire detection, victim localisation, continuous exchange of HD/UHD video and telemetry, and reliable coordination between aerial, ground and control-room assets. Traditional approaches often rely heavily on direct human intervention and can be constrained by limited accessibility, incomplete operational information and communication gaps in remote or obstructed areas.

The Greek use case addresses these challenges by combining B5G/6G technologies and exposed 3GPP network APIs with AI-enabled video analytics, a mission UAV (mUAV), a robotic dog/UGV, a dedicated relay UAV (rUAV), edge/Extreme-Edge processing and control-room functions. The objective is to reduce human exposure while improving early smoke/fire detection, victim localisation and prioritisation, collaborative aerial-ground search, service continuity in obstructed areas, and operational decision support. In particular, the relay UAV extends coverage by bridging PC5 sidelink connectivity from the robotic dog to Uu connectivity towards the gNB, while Energy Efficiency as a Service (EEaaS) supports monitoring and energy-aware operation of the overall solution.

Solutions/Trial scenarios to address the challenges

The trial scenarios demonstrate the use case innovations through an integrated operational storyline. In a remote forest or peri-urban forest area under wildfire risk, a 5G-connected HD/4K camera using CPE/Wi-Fi 6 provides a continuous video stream to AI functions for early smoke and fire detection (step 1 in Figure). A B5G/6G-enabled system with exposed 3GPP APIs supports network/service awareness and the provision of network information to application and AI functions. When a potential event is detected, alerts are sent to the control room, where a web-based interface provides live visualisation of the deployed cameras, access to previous events and service-performance awareness for the relevant stakeholders (2).

Once fire detection is confirmed, a victim-localisation workflow combines network-based location information from different cells with AI/analytics to estimate and prioritise possible casualty locations within the hazardous area (3). A mission UAV (mUAV) is dispatched to high-priority areas to provide aerial imagery and telemetry, while the robotic dog is deployed into dense vegetation, smoke-affected zones or other areas that may be difficult or unsafe for first responders to access directly (4). Live video streams from the mUAV and the robotic dog are processed by edge/Extreme-Edge AI functions for detection, tracking and event annotation, producing a continuously updated operational picture for the control room and first responders (5).

Where the robotic dog experiences insufficient or obstructed direct connectivity, a dedicated relay UAV (rUAV) provides coverage extension: the robotic dog establishes a PC5 sidelink to the rUAV, while the rUAV maintains Uu connectivity towards the gNB, effectively forming a PC5-Uu bridge and preserving video, telemetry and control/service continuity (6). The robotic dog can then approach the victim area, support victim localisation and communication, transport essential supplies where appropriate, and provide information to first responders, who receive the integrated operational picture for safer and better-informed SAR intervention (7).