Target following on nano-scale Unmanned Aerial Vehicles

Abstract

Unmanned Aerial Vehicles (UAVs) with high level autonomous navigation capabilities are a hot topic both in industry and academia due to their numerous applications. However, autonomous navigation algorithms are demanding from the computational standpoint, and it is very challenging to run them on-board of nano-scale UAVs (i.e., few centimeters of diameter) because of the limited capabilities of their MCU-based controllers. This work focuses on the object tracking capability, (i.e., target following capability) on such nano-UAVs. We present a lightweight hardware-software solution, bringing autonomous navigation on a commercial platform using only on-board computational resources. Furthermore, we evaluate a parallel ultra-low-power (PULP) platform that enables the execution of even more sophisticated algorithms. Experimental results demonstrate the benefits of our solution, achieving accurate target following using an ARM Cortex M4 microcontroller consuming ≈ 130mW. Our evaluation on a PULP architecture shows the proposed solution running up-to 60 frame-per second in a power envelope of ≈ 30mW leaving more than 70% of the computational resources free for further on-board processing of more complex algorithms.