Autonomous sense & avoid capabilities based on aircraft performances estimation

An autonomous navigation system integrating both the path following and the autonomous sense & avoid functions is presented in this article. The sense & avoid algorithm was developed to provide an avoidance manoeuvre that ensures a minimum separation between the ownship and all other agents during its execution in a multiple flying threats scenario. The resolution manoeuvre is defined as step variations in the heading angle and altitude autopilots commands. The commands are optimised in order to get the smallest step command necessary to keep a minimum predefined separation between the ownship and the threats. Its computation is based on the estimation of the future trajectory of all the agents and, therefore, on the estimation of aircraft performance during the manoeuvre. The suggested resolution manoeuvre is updated at 1 Hz in order to take into account any unpredictable changes of the threat trajectories. The obtained heading and altitude change commands are displayed on a novel human–machine interface to support the pilot in the planning of the avoidance action. The proposed sense & avoid system is modelled in a Matlab/Simulink® environment for a Piper J3 Cub 40 model aircraft. The threats considered are aircrafts that communicate their states to the system through their Automatic Dependent Surveillance-Broadcast mode S transponders.

[1]  Chi Kin,et al.  Real-time Trajectory Generation for Collision Avoidance with Obstacle Uncertainty , 2011 .

[2]  Paul Freeman,et al.  A Low Cost Phase Array Solution for UAV Collision Avoidance , 2010 .

[3]  Mykel J. Kochenderfer,et al.  Improved Monte Carlo Sampling for Conict Probability Estimation , 2010 .

[4]  Yiyu Yao Granular Computing for Web Intelligence and Brain Informatics , 2007 .

[5]  Mykel J. Kochenderfer,et al.  A Bayesian Approach to Aircraft Encounter Modeling , 2008 .

[6]  Jean-Paul Jamont,et al.  About Some Specificities of Embedded Multiagent Systems Design , 2007, IAT.

[7]  Antonios Tsourdos,et al.  UAV Conflict Detection and Resolution for static and dynamic obstacles , 2008 .

[8]  Giancarmine Fasano,et al.  Integrated Obstacle Detection System based on Radar and Optical Sensors , 2010 .

[9]  Fabrício Enembreck,et al.  Noise Tolerance in Reinforcement Learning Algorithms , 2007 .

[10]  Syed Irtiza Ali Shah,et al.  3D Obstacle Detection Using a Single Camera , 2009 .

[11]  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..

[12]  Mykel J. Kochenderfer,et al.  Hazard Alerting using Line-of-Sight Rate , 2008 .

[13]  Y.K. Kwang,et al.  Performance simulation of radar sensor based obstacle detection and collision avoidance for smart UAV , 2005, 24th Digital Avionics Systems Conference.

[14]  Donald E. Swihart,et al.  Autonomous Collision Avoidance System for Air-to-Air Operations , 2003 .

[15]  Clark N. Taylor,et al.  Obstacle Avoidance For Unmanned Air Vehicles Using Image Feature Tracking , 2006 .

[16]  Patrick Garrec,et al.  MIMO radar for sense and avoid for UAV , 2010, 2010 IEEE International Symposium on Phased Array Systems and Technology.

[17]  John Valasek,et al.  INTELLIGENT AGENT FOR AIRCRAFT COLLISION AVOIDANCE , 2001 .

[18]  James Archibald,et al.  On-Board Vision-Based Sense-and-Avoid for Small UAVs , 2008 .

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

[20]  B. M. Albaker,et al.  A survey of collision avoidance approaches for unmanned aerial vehicles , 2009, 2009 International Conference for Technical Postgraduates (TECHPOS).

[21]  Andrew Zeitlin Developing Requirements for the Unmanned Aircraft Sense and Avoid Function , 2009 .

[22]  Anthony J. Calise,et al.  Vision-Based Obstacle Avoidance for UAVs , 2007 .

[23]  A. Ganguli,et al.  On the Limits of Collision Detection Performance of a Sense- and-Avoid System for Non-Cooperative Air Traffic , 2010 .

[24]  J. Tadema,et al.  Self Separation Support for UAS , 2010 .

[25]  Michal P ˇ echouand,et al.  Convergence of Peer-to-Peer Collision Avoidance among Unmanned Aerial Vehicles , 2007 .

[26]  M. Grassi,et al.  AIAA Guidance, Navigation, and Control Conference , 2008 .

[27]  Dennis M. Coulter UAS Integration into the National Airspace System: Modeling the Sense and Avoid Challenge , 2009 .

[28]  M. Pechoucek,et al.  Agent-Based Multi-Layer Collision Avoidance to Unmanned Aerial Vehicles , 2007, 2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems.

[29]  Essameddin Badreddin,et al.  Collision avoidance in a recursive nested behaviour control structure for Unmanned Aerial Vehicles , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[30]  Dennis M. Coulter,et al.  Encounter Analysis to Support Detect, Sense, and Avoid (DSA) Elevation Field of Regard (FOR) Requirements , 2007 .

[31]  Richard R. Schultz,et al.  Unmanned Aircraft Systems Sense and Avoid Avionics Utilizing ADS -B Transceiver , 2009 .