International Workshop on Robotics for risky interventions and Environmental Surveillance-Maintenance (VRISE)

Recent armed conflicts (Ukraine, Afghanistan, Iraq, Syria) have seen a dramatic rise in the use of EOs (Explosive Ordnance), specifically IEDs (Improvised Explosive Devices) and landmines by adversaries, often resulting in casualties from EU and NATO member states. In modern warfare operations, consistently 50% of all soldier deaths in action are related to IEDs. Therefore, the Royal Military Academy is working on a research project, called AIDED, on the development of Artificial Intelligence (AI) for the detection of explosive devices. AIDED will use a set of state of the art Artificial Intelligence algorithms able to identify unconventional (IEDs) and conventional (buried mines) explosive devices, and autonomously plan offline and run-time missions plans. AI-Machine Learning techniques such as deep learning will be designed & trained using simulated & outdoor data sets for the detection of EOs using sensor data from Ground Penetrating Radar, Electromagnetic Arrays, infrared and thermal cameras and Laser Induced Breakdown Spectroscopy. Sensor data will be fused to improve the confidence of detection and classification of EOs by removing outliers and false detection. AI techniques will ensure robustness to changing environments & composition of EOs. AIDED will also develop AI based Centralized & decentralized mission planning to coordinate a swarm of small and medium heterogeneous robots (land and aerial) that are capable of working cooperatively towards the goal of detecting EOs that are on the surface, buried or hidden. The Positioning Navigation and Mapping will also be based on AI-machine learning techniques for robustness and standalone operation in GNSS denied environments