ISSN: 2375-3846
American Journal of Science and Technology  
Manuscript Information
 
 
Operation Oriented Path Planning Strategies for Rpas
American Journal of Science and Technology
Vol.2 , No. 6, Publication Date: Dec. 11, 2015, Page: 321-328
1254 Views Since December 11, 2015, 1003 Downloads Since Dec. 11, 2015
 
 
Authors
 
[1]    

Giorgio Guglieri, Department of Mechanical and Aerospace Engineering, Corso Duca degli Abruzzi, Torino, Italy.

[2]    

Alessandro Lombardi, Department of Mechanical and Aerospace Engineering, Corso Duca degli Abruzzi, Torino, Italy.

[3]    

Gianluca Ristorto, Department of Science and Technology, Piazza Università, Bolzano, Italy.

 
Abstract
 

Due to the recent spread of RPAS into the national airfields, civil aviation authorities are actively involved in the development of regulations for RPAS, especially for small vehicles with mass less than 150 kg. These regulations often require that the RPAS operators perform a risk analysis to assess the level of risk of the operations. The paper considers the Italian regulation and describes the implementation of the RPAS risk analysis method proposed by ENAC into a 2D flight path planning software for UAV that is called JavaCube. This tool is able to generate waypoint-based paths based on graph search algorithms which incorporate the risk analysis model within their cost function so that the risk for the aircraft of occurring in catastrophic failure is minimized. The resulting paths are shown on a risk map that is generated according to UAV data, flight altitude and the population density distribution of the overflown area. This tool could provide a useful UAV path planner that meets the requirements of the current Italian regulation.


Keywords
 

RPAS, Path Planning, Collision Avoidance, Risk Analysis


Reference
 
[01]    

Ente Nazionale per l’Aviazione Civile. Mezzi Aerei a Pilotaggio Remoto. 2015.

[02]    

Unmanned Aerial Systems in European Airspace. Safety Aspects of Civil RPAS Operations. 2013.

[03]    

JAA/EUROCONTROL RPAS Task Force. A concept for European Regulations for Unmanned Aerial Vehicles (RPAS). 2004.

[04]    

NATO. UAV Systems Airworthiness Requirements. 2007.

[05]    

E. Pastor, M. Perez-Batlle, P. Royo, R. Cuadrado and C. Barrado. Preparing for an Unmanned Future in SESAR. Real-time Simulations of RPAS Missions. Proceedings of III SESAR Innovation Days, Stockholm, Sweden, 2013.

[06]    

E. Pastor, M. Perez-Batlle, P. Royo, R. Cuadrado and C. Barrado. Real-time Simulations to Evaluate the RPAS integration in Shared Airspace. Proceedings of IV SESAR Innovation Days, Madrid, Spain, 2014.

[07]    

E. Rudnik-Cohen, J. W. Hermann, S. Azarm. Risk-based Path Planning Optimization Methods for UAV over Inhabited Areas. ASME 2015 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Boston, USA, 2015.

[08]    

Federal Aviation Administration. Expected Casualty Calculations for Commercial Space Launch and Reentry Missions. FAA–AC431.35, 2000.

[09]    

K. Dalamagkidis, K.P. Valavanis and L.A. Piegl. Evaluating the Risk of Unmanned Aircraft Ground Impacts. In Proceedings of the 16th Mediterranean Conference on Control and Automation, Ajaccio, France, 2008.

[10]    

K. Dalamagkidis, K.P. Valavanis and L.A. Piegl. On Integrating Unmanned Aircraft Systems into the National Airspace System. Springer ed., 2012.

[11]    

G. Guglieri, F. Quagliotti and G. Ristorto. Operational Issues and Assessment of Risk for Light UAVs. Springer ed., 2012. Journal of Unmanned Vehicle Systems, Vol. 2, n. 4, 2014.

[12]    

L.F. Bertuccelli and J.P. How. Robust UAV Search for Environmentas with Imprecise probability Maps. Proceedings of IEEE Conference of Decision and Control, Seville, Spain, 2005.

[13]    

D. Ferguson and A. Stentz. Using interpolation to improve path planning: The Field D* algorithm. Journal of Field Robotics, Vol. 23, n. 2, pp. 79–101, 2006.

[14]    

K. Daniel, A. Felner, S. Koenig and A. Nash. Theta*: Any–Angle Path Planning on Grids. Journal of Artificial Intelligence Research, Vol. 39, pp. 533–579, 2010.

[15]    

S. Mittal and K. Deb. Three–Dimensional Offline Path Planning Strategies for UAVs Using Multi–objective Evolutionary Algorithms. Congress on Evolutionary Computation, Singapore, 2007.

[16]    

D. Jia and J. Vagners. Parallel Evolutionary Algorithms for UAV Path Planning. AIAA 1st Intelligent Systems Technical Conference, Chicago, USA, 2004.





 
  Join Us
 
  Join as Reviewer
 
  Join Editorial Board
 
share:
 
 
Submission
 
 
Membership