Abschluss des KIRAS FFG Projekts NIKE MATE

The NIKE MATE (Human Machine Navigation Teaming) project focuses on the precise positioning of emergency responders in urban environments to prevent unintentional collisions when using autonomous systems. In particular, the project focused on determining the position of people in environments without GNSS and corresponding infrastructure.

The research focused on three aspects: improved positioning through a collaborative approach, visualisation of positions for commanders, and investigation of psychological challenges in such complex scenarios. At the beginning of the project, the existing Pedestrian Dead Reckoning (PDR) model was examined. The memory requirements of the AI model were reduced, and different quantizations were compared to train the chosen concept with newly collected training data. This enables the differentiation of eight types of movement. An innovative pseudolite positioning method was also investigated to enable the transmission of global coordinates into the tunnel interior. Four synchronized bladeRF transmitters send out a replica generated by OHB, which an adapted receiver uses to determine the position in the WGS84 coordinate system. Practical tests proved successful. Further development focused on the positioning of actors within the tunnel. A collaborative concept was developed that estimates the position of robots and people using a factor graph. This combines UWB distance measurements, IMU steps, LiDAR SLAM, and radio odometry with corresponding error models. The positions are processed centrally on the robot and forwarded to the XR COMMAND guidance information system for visualization. This allows for a visualisation in an XR (Extended Reality) environment.

Test measurements at the Zentrum am Berg verified the chosen concept and served as an evaluation tool. Distances between actors and wall-mounted anchors were successfully fused with additional sensors in a UWB network to estimate and visualize positions (human and robot) in real time. The collaborative approach, combined with the robot’s sensors, enables a stable estimation even outside the initial infrastructure.

Helmut Schmidt University Hamburg has investigated and assessed the psychological effects on soldiers deployed in urban infrastructure.