THESIS COLLOQUIUM

1. THESIS COLLOQUIUM Collision avoidance and coalition formation of multiple unmanned aerial vehicles in high density traffic environments Joel George M

2. “… it was nevertheless - the first time in the history of the world in which a machine carrying a man had raised itself by its own power into the air in full flight, had sailed forward without reduction of speed, and had finally landed at a point as high as that from which it started.” Orville Wright Details of first flight: Speed = 6.8 miles/hour Range = 120 feet Altitude = 10 feet

3. Slogan of aircraft design industry Faster, Farther, Higher (and Safer) Boundaries of speed, altitude, range, and endurance have been pushed further and further

4. Aircraft kept the tag “machine carrying a man” Presence of man in aircraft was always an important design consideration

5. “Elimination of pilot from a manned combat aircraft removes many of the conventional design constraints … This at once throws open the design parameter space and dramatic improvements in performance measures like increased speed, range, maneuverability, and payload can be achieved.” Late Dr. S Pradeep

6. Why Unmanned Aerial Vehicles (UAVs)? In some missions, human presence ‘need not’ be there In some other missions, human presence ‘should not’ be there Unmanned Aerial Vehicles find applications in Dull, Dirty, and Dangerous missions

7. Why UAVs? Factors compelling the use of Unmanned Aerial Vehicles (UAVs) Design freedom (mission specific designs) Dull, dirty, and dangerous missions Low cost, portability, absence to human risk, …

8. Why autonomous UAVs? UAVs can be remotely piloted However, desirable to make UAVs autonomous

9. Why multiple UAVs? UAVs are often small Some missions are more effectively done by multiple UAVs Use of multiple UAVs leads to coordination problems Collision avoidance, coalition formation, formation flying, …

10. This thesis addresses the problems of Collision avoidance, Coalition formation, and Mission involving collision avoidance and coalition formation of multiple UAVs in high density traffic environments

11. OUTLINE CHAPTER 1 Introduction CHAPTER 2 Collision avoidance among multiple UAVs CHAPTER 3 Collision avoidance with realistic UAV models CHAPTER 4 Coalition formation with global communication CHAPTER 5 Coalition formation with limited communication CHAPTER 6 Coalition formation and collision avoidance in multiple UAV missions CHAPTER 7 Conclusions

12. CHAPTER 1 Introduction

13. Collision avoidance Using information of positions and velocities of UAVs in the sensor range, a UAV needs to find an efficient safe path to destination A safe path means that no UAV should come within each others safety zones during any time of flight Efficiency  less deviation from nominal path

14. Collision avoidance literature Have been looked at from the robotics and air traffic management points of view Ground based robots can stop to finish the calculations Collision avoidance algorithms addressing air traffic management problems consider only a few aircraft

15. A situation requiring three dimensional collision avoidance

16. Coalition formation Multiple UAVs with limited sensor ranges search for targets A target found needs to be prosecuted A UAV that detected the target may not have sufficient resources ‘Need to talk’ to other UAVs to form a coalition for target prosecution Objective: To find and prosecute all targets as quickly as possible The algorithm should be scalable

17. Coalition formation literature • Multi-agent coalition formation • Can share resources • Extensive communication • Multi-robot coalition formation • Resources do not deplete • Multi-UAV coalition formation • Resources deplete with use • Need quick coalition formation algorithms

18. Collision avoidance and coalition formation in multiple UAV missions Multi-UAV rendezvous with collision avoidance Coalition formation with collision avoidance

19. CHAPTER 2 Collision avoidance among multiple UAVs

20. Assumptions UAV kinematic model Constant speed Minimum radius of turn Further assumption Limited sensor range

21. It suffices, in case of a multiple UAV conflict, for a UAV to avoid the most imminent near miss to obtain a good collision avoidance performance.

22. Two UAVs within each others safety zones results in a ‘near miss’ Objective is to reduce the number of near misses, as in a high density traffic case, it may not be possible to avoid near misses Lesser the number of near misses, better the collision avoidance algorithm Aircraft deviates from its nominal path due to collision avoidance maneuver. Efficiency = Lesser the deviation (higher efficiency), better the collision avoidance algorithm

23. UAVs encounter multiple conflicts Reduce multiple conflicts to an ‘effective’ one-one conflict by finding the ‘most threatening’ UAV from among the ones in sensor range Most threatening UAV: A UAV U2 is the most threatening UAV for U1 at an instant of time, if U2 is in the sensor range of U1 Predicted miss distance between U1 and U2 suggests the occurrence of a near miss Out of all the UAVs in the sensor range of U1 with which U1 has a predicted near miss, the near miss with U2 is the earliest to occur

24. Collision avoidance maneuver A necessary condition for collision between two aircraft to occur is that the Line of Sight (LOS) Rate between them be zero For collision avoidance, a UAV does a maneuver to increase the LOS rate Each UAV does a maneuver to avoid collision with the most threatening neighbor

25. Two Dimensional Reactive Collision Avoidance: RCA-2D

26. Simple head-on collisions

27. High density traffic

28. Random flight test Aircraft fly from random points on outer circle to random points on inner circle Velocity: 500 miles per hour Turn rate: 5 degrees per second Radius of outer circle 120 miles Radius of inner circle 100 miles

29. Archibald, J. K., Hill, J. C., Jepsen, N. A., Strirling, W. C., & Frost, R. L. (2008). A satisficingapproach to aircraft conflict resolution. IEEE Transactions on System, Man, and Cybernetics - Part C: Applications and Reviews, 38, 510–521. Since the test case involves random flights, the simulations are run 20 times for each case, and the values presented are averaged over the results obtained from these runs

30. Effect of noise in position measurement

31. Three dimensional engagement Collision plane RCA-3D-I Three dimensional collision avoidance algorithms RCA-3D-O

32. Comparison of the performance 2D and 3D algorithms for random flights

33. Modified random flights (three dimensional) Case 1: h = 20 miles, rin= 100 miles, and rout = 120 miles Case 2: h = 60 miles, rin= 55 miles, and rout = 70 miles Case 3: h = 100 miles, rin= 40 miles, and rout = 50 miles

34. Summary of Chapter 2 Developed conceptually simple collision avoidance algorithms For two and three dimensional conflicts For high density traffic environments Analyzed the performance of these algorithms

35. CHAPTER 3 Collision avoidance with realistic UAV models

36. Realistic UAV Model UAV of span 1.4224 m, weighing 1.56 kg • Stability and control derivatives from Aviones • A UAV flight simulator developed by the Brigham Young University • (an open source software) • Available: http://aviones.sourceforge.net/ The Zagi Aircraft www.zagi.com Span = 1.5 m Mean Chord = 0.33 m Weight = 1.5 kg Picture courtesy: www.zagi.com

37. UAV control system Controllers designed through successive loop closure Separate controllers for holding altitude, attitude, and speed PI controllers with parameters tuned manually

38. Controller design Altitude hold controller Similar controllers for attitude and speed holds are designed

39. Implementing the guidance commands Look-up graph for bank angle that will provide required turn rate

40. Test of collision avoidance A example of collision avoidance of 5 UAVs The test case is set-upsuch that the avoidance of one conflict will lead into another

41. Test case of random flights for dense traffic Random flights test case inner circle radius 400 m outer circle radius 500 m velocity 12 m/s maximum turn rate 10 deg/sec. Any approach of two UAVs within 10 m is considered a near miss An approach within 2 m is a collision.

42. Results of the random flight test case

43. Implementation of 3D collision avoidance algorithm Realization of pitch and turn rate commands

44. Pitch rate guidance and control loops

45. Results of the random flight test case for homogeneous UAVs for heterogeneous UAVs

46. Collision avoidance in presence of non-cooperating UAVs

47. Summary of Chapter 3 Implemented collision avoidance algorithms on 6 DoF UAV models Simulations with heterogeneous and non-cooperating UAVs

48. CHAPTER 4 Coalition formation with global communication

49. Coalition formation for search and prosecute mission Search targets and destroy them The targets may have different requirements Objectives: • Destroy the target is minimum time • Coalition should have minimum number of UAVs • Rendezvous on target to inflict maximum damage

50. Assumptions Limited sensor radius Target locations are not know a priori Limited resources that deplete with use Stationary targets Global communication