This paper tackles the problem of strategic path planning in high density urban environment. Safe paths with respect to fixed and moving obstacles are defined for a set of UAVs by accounting for navigation and control errors in the definition of the minimum separations. Strategic path definition consists in two steps, i.e., global and local planning, which are aimed first at defining the path to avoid fixed obstacles, and then at refining it accounting for the deconfliction with moving obstacles, respectively. Deconfliction is handled by dealing with time varying occupancy maps where the moving obstacles are represented by their actual trajectory inflated with safety margins and 4D trajectory (position and time) errors. GNSS coverage and UAV on-board equipment, i.e., navigation system performance, impact positioning errors and thus the margins considered in the planning process. Therefore, better equipped UAVs are expected to enable more efficient replanning and airspace utilization. The algorithm is tested in a simulation scenario taken from real world environment and chosen with the aim of highlighting navigation issues at the (low) altitudes where the UAVs are demanded to fly.
Safe planning and deconfliction for multiple UAVs in high density low altitude urban environments / Causa, F.; Fasano, G.. - 2021-:(2021), pp. 1-10. (Intervento presentato al convegno 40th IEEE/AIAA Digital Avionics Systems Conference, DASC 2021 tenutosi a usa nel 2021) [10.1109/DASC52595.2021.9594489].
Safe planning and deconfliction for multiple UAVs in high density low altitude urban environments
Causa F.
Primo
;Fasano G.Ultimo
2021
Abstract
This paper tackles the problem of strategic path planning in high density urban environment. Safe paths with respect to fixed and moving obstacles are defined for a set of UAVs by accounting for navigation and control errors in the definition of the minimum separations. Strategic path definition consists in two steps, i.e., global and local planning, which are aimed first at defining the path to avoid fixed obstacles, and then at refining it accounting for the deconfliction with moving obstacles, respectively. Deconfliction is handled by dealing with time varying occupancy maps where the moving obstacles are represented by their actual trajectory inflated with safety margins and 4D trajectory (position and time) errors. GNSS coverage and UAV on-board equipment, i.e., navigation system performance, impact positioning errors and thus the margins considered in the planning process. Therefore, better equipped UAVs are expected to enable more efficient replanning and airspace utilization. The algorithm is tested in a simulation scenario taken from real world environment and chosen with the aim of highlighting navigation issues at the (low) altitudes where the UAVs are demanded to fly.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.