The demand for autonomous nano-sized Unmanned Aerial Vehicles (UAVs) has risen due to their small size and agility, allowing for flight in cluttered indoor environments. However, their small size also significantly limits the payload as well as the battery size and computational resources. Especially the scarcity of memory poses a significant obstacle to generating high-resolution occupancy maps. This work presents an onboard 2-dimensional occupancy mapping system for centimeterscale UAVs using a miniature 64-zone Time of Flight sensor. Experimental evaluations on the Crazyflie 2.1 nano-UAV have demonstrated that produced maps feature a resolution of 10cm at mapping velocities up to 1.5m/s, while covering an area of maximum 400m(2).
Polonelli, T., Feldmann, C., Niculescu, V., Müller, H., Magno, M., Benini, L. (2023). Towards Robust and Efficient On-board Mapping for Autonomous Miniaturized UAVs. 345 E 47TH ST, NEW YORK, NY 10017 USA : IEEE [10.1109/IWASI58316.2023.10164476].
Towards Robust and Efficient On-board Mapping for Autonomous Miniaturized UAVs
Polonelli, Tommaso;Magno, Michele;Benini, Luca
2023
Abstract
The demand for autonomous nano-sized Unmanned Aerial Vehicles (UAVs) has risen due to their small size and agility, allowing for flight in cluttered indoor environments. However, their small size also significantly limits the payload as well as the battery size and computational resources. Especially the scarcity of memory poses a significant obstacle to generating high-resolution occupancy maps. This work presents an onboard 2-dimensional occupancy mapping system for centimeterscale UAVs using a miniature 64-zone Time of Flight sensor. Experimental evaluations on the Crazyflie 2.1 nano-UAV have demonstrated that produced maps feature a resolution of 10cm at mapping velocities up to 1.5m/s, while covering an area of maximum 400m(2).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
