Multi-Sensor Cooperative Robots for Shallow Buried Explosive Threat Detection: System Architecture, Mission Strategy, and Test Field Results

We describe a new paradigm using cooperating robots and multi-sensor data fusion for surficial and buried plastic and metal-cased landmine detection. The system operates remotely minimizing risk for the operator. With this architecture, it is possible to plan a mission, optimize sensor settings, and visualize the data from a remote computer or handheld device. The sensors were installed on three robotic platforms: microwave radars (Robots #1 and #3), LiDAR (Robot #1 and Robot #3), high-resolution optical camera (Robot #1), and metal detector (Robot #2). The acquisition and processing of multisensor information and application of AI demonstrated effective detection and classification of buried small low metal content landmines (e.g., M-14 and Type-72 mines) and scatterable surface mines like the PFM-1 “butterfly”. For continuing safe operation, the system also requires detection of tripwires that are commonly rigged to explosive devices to protect minefields. For this purpose, the first robot uses an optical sensor and an algorithm trained to detect sub-horizontal line segments that could be metal or nylon wires. All robots are equipped with GNSS providing mapping of targets with accuracy better than 10 cm. Based on optimization of sensor power consumption, the operating time for each robot is on the order of hours.