Sense and avoid for Unmanned Aerial Vehicles using ADS-B

We present the design and implementation of an aircraft collision avoidance algorithm for Unmanned Aerial Vehicles (UAVs). Automatic Dependent Surveillance-Broadcast (ADS-B) is used to detect aircraft. The UAV needs to fly through pre-assigned waypoints while avoiding collisions with other aircraft. The aircraft are indifferent to the UAV. A collision with aircraft are detected by simulating the UAV's trajectory along the path of assigned waypoints using its closed-loop dynamics. A sampling based algorithm is used for collision avoidance path planning. A second collision check is performed on the generated path with the updated UAV and aircraft's states. The path will be re-planned if it leads to a collision. The algorithm was validated in Software-In-the-Loop Simulation (SITL). ADS-B data obtained from commercial aircraft flying over the Phoenix Skyharbor airport were used for simulating the collisions. The paper shows that the algorithm enables the UAV to avoid multiple aircraft with different approaching angles and speeds.

[1]  Weiyi Liu,et al.  Probabilistic Aircraft Midair Conflict Resolution Using Stochastic Optimal Control , 2014, IEEE Transactions on Intelligent Transportation Systems.

[2]  Jason J. Ford,et al.  Airborne vision‐based collision‐detection system , 2011, J. Field Robotics.

[3]  Luis Mejias,et al.  Omnidirectional bearing-only see-and-avoid for small aerial robots , 2011, The 5th International Conference on Automation, Robotics and Applications.

[4]  Al Savvaris,et al.  Autonomous sense & avoid capabilities based on aircraft performances estimation , 2014 .

[5]  Paul J. Goulart,et al.  Real-Time Trajectory Generation for Aircraft Avoidance Maneuvers , 2009 .

[6]  Eric N. Johnson,et al.  Minimum-Effort Guidance for Vision-Based Collision Avoidance , 2006 .

[7]  Jonathan P. How,et al.  Motion Planning in Complex Environments using Closed-loop Prediction , 2008 .

[8]  Jonathan P. How,et al.  Aircraft trajectory planning with collision avoidance using mixed integer linear programming , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[9]  Jonathan P. How,et al.  Probabilistically safe motion planning to avoid dynamic obstacles with uncertain motion patterns , 2013, Auton. Robots.

[10]  Sebastian Scherer,et al.  Flying Fast and Low Among Obstacles: Methodology and Experiments , 2008, Int. J. Robotics Res..

[11]  Jonathan P. How,et al.  A New Nonlinear Guidance Logic for Trajectory Tracking , 2004 .

[12]  Howie Choset,et al.  Principles of Robot Motion: Theory, Algorithms, and Implementation ERRATA!!!! 1 , 2007 .

[13]  Peter Thomas,et al.  On-board trajectory generation for collision avoidance in unmanned aerial vehicles , 2011, 2011 Aerospace Conference.

[14]  Jur P. van den Berg,et al.  Reciprocal collision avoidance for robots with linear dynamics using LQR-Obstacles , 2013, 2013 IEEE International Conference on Robotics and Automation.

[15]  Christian Laugier,et al.  Navigation Among Moving Obstacles Using the NLVO: Principles and Applications to Intelligent Vehicles , 2005, Auton. Robots.

[16]  Mykel J. Kochenderfer,et al.  Aircraft Collision Avoidance Using Monte Carlo Real-Time Belief Space Search , 2011, J. Intell. Robotic Syst..

[17]  Jonathan P. How,et al.  Real-Time Motion Planning With Applications to Autonomous Urban Driving , 2009, IEEE Transactions on Control Systems Technology.

[18]  Al Savvaris,et al.  Autonomous collision avoidance based on aircraft performances estimation , 2011, 2011 IEEE/AIAA 30th Digital Avionics Systems Conference.

[19]  Marin Kobilarov,et al.  Cross-entropy motion planning , 2012, Int. J. Robotics Res..

[20]  Luis Mejías Alvarez,et al.  A 3D Collision Avoidance Strategy for UAVs in a Non-Cooperative Environment , 2013, J. Intell. Robotic Syst..

[21]  Andrey M. Shevchenko.  Energy-based approach for flight control systems design , 2013, Autom. Remote. Control..

[22]  Ross A. Knepper,et al.  Differentially constrained mobile robot motion planning in state lattices , 2009, J. Field Robotics.

[23]  Stefan Hrabar,et al.  Reactive obstacle avoidance for Rotorcraft UAVs , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[24]  E. Feron,et al.  Real-time motion planning for agile autonomous vehicles , 2000, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[25]  Miguel A. Olivares-Méndez,et al.  Robust real-time vision-based aircraft tracking from Unmanned Aerial Vehicles , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[26]  Sanjiv Singh,et al.  Passive, Long-Range Detection of Aircraft: Towards a Field Deployable Sense and Avoid System , 2009, FSR.

[27]  S. Sastry,et al.  An Evasive Maneuvering Algorithm for UAVs in See-and-Avoid Situations , 2007, 2007 American Control Conference.

[28]  Jur P. van den Berg,et al.  Anytime path planning and replanning in dynamic environments , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[29]  Jean-Claude Latombe,et al.  Randomized Kinodynamic Motion Planning with Moving Obstacles , 2002, Int. J. Robotics Res..

[30]  Peter I. Corke,et al.  Image processing algorithms for UAV "sense and avoid" , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[31]  Paolo Fiorini,et al.  Motion Planning in Dynamic Environments Using Velocity Obstacles , 1998, Int. J. Robotics Res..

[32]  Dinesh Manocha,et al.  LQG-obstacles: Feedback control with collision avoidance for mobile robots with motion and sensing uncertainty , 2012, 2012 IEEE International Conference on Robotics and Automation.

[33]  Leslie Pack Kaelbling,et al.  Collision Avoidance for Unmanned Aircraft using Markov Decision Processes , 2010 .

[34]  Mykel J. Kochenderfer,et al.  Unmanned Aircraft Collision Avoidance using Continuous-State POMDPs , 2011, Robotics: Science and Systems.

[35]  S. Saripalli,et al.  Path planning using 3D Dubins Curve for Unmanned Aerial Vehicles , 2014, 2014 International Conference on Unmanned Aircraft Systems (ICUAS).