We propose a shortest trajectory planning algorithm imple-mentation for Unmanned Aerial Vehicles (UAVs) on an em-bedded GPU. Our goal is the development of a fast, energy-efficient global planner for multi-rotor UAVs supporting hu-man operator during rescue missions. The work is based on OpenCL parallel non-deterministic version of the Dijkstra algorithm to solve the Single Source Shortest Path (SSSP). Our planner is suitable for real-Time path re-computation in dynamically varying environments of up to 200 m2. Results demonstrate the effcacy of the ap-proach, showing speedups of up to 74x, saving up to 98% of energy versus the sequential benchmark, while reaching near-optimal path selection, keeping the average path cost error smaller than 1.2%.
An energy-efficient parallel algorithm for real-Time near-optimal UAV path planning / Palossi, Daniele; Furci, Michele; Naldi, Roberto; Marongiu, Andrea; Marconi, Lorenzo; Benini, Luca. - STAMPA. - (2016), pp. 392-397. (Intervento presentato al convegno ACM International Conference on Computing Frontiers, CF 2016 tenutosi a Como, Italy nel 16-19 May 2016) [10.1145/2903150.2911712].
An energy-efficient parallel algorithm for real-Time near-optimal UAV path planning
PALOSSI, DANIELE;FURCI, MICHELE;NALDI, ROBERTO;MARONGIU, ANDREA;MARCONI, LORENZO;BENINI, LUCA
2016
Abstract
We propose a shortest trajectory planning algorithm imple-mentation for Unmanned Aerial Vehicles (UAVs) on an em-bedded GPU. Our goal is the development of a fast, energy-efficient global planner for multi-rotor UAVs supporting hu-man operator during rescue missions. The work is based on OpenCL parallel non-deterministic version of the Dijkstra algorithm to solve the Single Source Shortest Path (SSSP). Our planner is suitable for real-Time path re-computation in dynamically varying environments of up to 200 m2. Results demonstrate the effcacy of the ap-proach, showing speedups of up to 74x, saving up to 98% of energy versus the sequential benchmark, while reaching near-optimal path selection, keeping the average path cost error smaller than 1.2%.File | Dimensione | Formato | |
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