Towards a Multi-Pixel Time-of-Flight Indoor Navigation System for Nano-Drone Applications
Vlad Niculescu, Hanna Muller, Iman Ostovar, Tommaso Polonelli, Michele Magno, Luca Benini
Abstract
Unmanned aerial vehicles (UAVs) have recently attracted the industry’s attention due to their numerous civilian and potential commercial applications. A promising UAV subclass includes nano and micro UAVs, characterized by centimeter size, few grams of payload and extremely limited on-board computational resources. Those features pose major challenges to enable autonomous navigation or even more basic relevant subtasks, such as reliable obstacle avoidance. This paper explores and characterizes a multi-zone Time of Flight (ToF) sensor to enhance autonomous navigation with a significantly lower computational load than most common visual-based solutions. In particular, the state-of-the-art integrated ToF sensor is characterized for the first time in literature in-field using an ad hoc lightweight PCB and the Crazyflie nano-UAV. The paper focuses, on the 8x8 pixel configuration, to detect obstacles up to 3m with centimeter accuracy and a frame rate up to 15 fps. The paper presents a solution for computing the approaching angle, crucial for many UAV tasks, with a maximum error of ±6°. Furthermore, relying on empirical data, the paper proposes a lightweight approach to calculate collision probability from each ToF sensor frame. This work aims to pave the way for future nano-UAV camera-less compact navigation solutions capable of extracting complex environmental features directly on-board.