Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93573
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Title: UnmannedSim : urban and multi-agent navigation network-enabled drones simulator for path planning and localization research
Authors: Ahad, S 
Shiu, WCL 
Huang, XY 
Sajid, DMZ 
Lee, MJL 
Su, M 
Hsu, LT 
Issue Date: 2021
Source: Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021), St. Louis, Missouri, September 2021, p. 1217-1227
Abstract: The possibility of deploying unmanned aerial vehicles (UAV) for smart city applications has sparked great interest in recent times. High-density cities like Hong Kong, Tokyo and New York have been moving forward to automation to lighten the load of the cities, as well as to provide a time saving, yet safe environment for their citizens. Simulating such UAV activities before practical implementation has therefore turned into a necessity. However, simulation of cities through traditional methods do not replicate the real-life errors in navigation caused by high-density tall buildings, variable wind speed, GNSS sensor measurement errors and other factors. In our research, we have built a new simulator named UnmannedSim which utilizes popular existing software packages such as AirSim and Unreal Engine while adding real-life errors to the simulator.
Publisher: Institute of Navigation
ISBN: 9780936406299
DOI: 10.33012/2021.18057
Description: 34th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 2021), September 20-24, 2021, St. Louis, Missouri
Rights: Posted with permission of the author.
The following publication Ahad, Sugata, Shiu, Wai Ching Lucas, Huang, Xin Yue, Sajid, DM Zahin, Lee, Max Jwo Lem, Su, Meiling, Hsu, Li Ta, "UnmannedSim: Urban and Multi-Agent Navigation Network-Enabled Drones Simulator for Path Planning and Localization Research," Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021), St. Louis, Missouri, September 2021, pp. 1217-1227 is first published by the Institute of Navigation and is available at https://doi.org/10.33012/2021.18057.
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