Development of a Testbed for Autonomous Navigation of an Off-Shelf Quadrotor Based on Ultra-Wide-Band Real-Time Localization - Gachoki, Nelson Muchiri; Kamau, Stanley; Ikua, Bernard (Association for Scientific Computing Electronics and Engineering (ASCEE), 2025)
Recent advances in autonomous aerial vehicle research, from theoretical simulations to experimental validations, has triggered demand for reliable proof-of-concept test-beds. Although such test-beds have been developed in some advanced drone research laboratories, their cost, expertise and complexity place them out of reach for upcoming research teams. This raises the need for development of less complex and affordable testbeds for quadrotor research. The contribution of this research is provision of low-cost autonomous quadrotor test-bed for proof-of-concept. The development of the proposed testbed entails configuration of Ultra-Wide-Band (UWB) based Real-Time Localization System (RTLS) to transmit position data of multiple agents to LabVIEW software for analysis and decision making. The autonomous navigation commands for the quadrotor are generated from the LabVIEW software and relayed through customized USB interface to the flight control module. The commands alter the digital state of Arduino board pins which are connected to the flight controller hence manipulating navigation pitch and roll parameters. The validation tests performed in the test-bed involved quadrotor hover and navigation in pursuit of the ground agent. The results demonstrate that UWB based RTLS achieves high precision of 99% when the modules are stationary but the precision reduced to 90% when the modules were in motion, which may be attributed actuating signal transmission delays. The results also showed that the Arduino based electronic flight controller is capable of generating flight paths to follow the ground robot in real-time with precision deviations of under 10% which is at par with other research test beds. This novel testbed provides a costeffective and accurate solution for autonomous flight testing, with precision comparable to visual-based testbeds, but at a much lower cost. Further research is encouraged to explore how the system performs with more than two agents and on a wider test arena.