Flight Test Setup for Cooperative Swarm Navigation in Challenging Environments using UWB, GNSS, and Inertial Fusion

This paper describes a basic framework for cognitive and collaborative navigation of small Unmanned Aerial Vehicles (sUAVs) with a focus on operation in challenging environments where GNSS performance may be deteriorated or even unavailable. The basic framework is based on a dynamic decision system where swarm members, a.k.a. agents, collect local sensor data and data from other agents in the swarm, to estimate the absolute and relative pose state of the swarm and its members and, hence, get better situational awareness to make decision that maintain safety but also satisfy the mission objectives. The paper discusses one possible way to integrate this swarm information using factor graphs and non-linear solvers. Simulation results will show the initial effectiveness of this method within the current architecture. The paper will, furthermore, describe the hardware and software architecture of the TU Berlin swarm test sUAVs and focus on the common GNSS, IMU, range radio board (SwarmEx) that forms the common core of the platforms' sensor payloads. Some initial results of the range radio performance will be included as well. Finally, the flight test environment will be described.