Current Challenges in UAS Research Intelligent Navigation and Sense & Avoid

Transcription

1 Current Challenges in UAS Research Intelligent Navigation and Sense & Avoid Joerg Dittrich Institute of Flight Systems Department of Unmanned Aircraft

2 UAS Research at the German Aerospace Center, Braunschweig Institute of Flight Systems Dept. Unmanned Aircraft (Jörg Dittrich) Operation of flying demonstrators Development of autonomous functions Vision-Based Flight Control flight control solutions for unmanned aircraft Systems for Unmanned Aircraft Evaluation capabilities for UAS Institute of Flight Guidance Dept. Pilot Assistance Systems (Bernd Korn) Controlled Airspace Integration Sense & Avoid ATM-concepts and procedures Ground Control Station Human-Machine-Interface Control of multiple UAVs Further work in structures and aerodynamics: Institute of Composite Structures and Adaptronics Institute of Aerodynamics and Flow Technology Slide 2

3 Institute of Flight Systems Research using Large Test Facilities The flying test beds Simulation Flight control system rig Rotor test in wind tunnel Slide 3

4 Our Fleet for UAS Research Slide 4

5 Airspace Integration - The big problem of UAS Most significant for Unmanned Aircraft Operations: When weather conditions permit, regardless of whether an operation is conducted under instrument flight rules or visual flight rules, vigilance shall be maintained by each person operating an aircraft as to see and avoid other aircraft. (FAR b) FAA position on UAS operations: Unmanned Aircraft Operations should require the proponent to provide the UA with a method that provides an equivalent level of safety, comparable to see-and-avoid requirements for manned aircraft Challenge: What is the equivalent level of safety? many workgroups (EUROCAE, NATO, FAA, EASA, etc...) many answers! What does a certifiable Sense & Avoid System look like? Slide 5

6 Installation of S&A Sensors on DLR s ATTAS Radar Sensor Optical Sensor 1st Flight Implementation Modified Radome CAD-Design Slide 6

7 Flight Tracks with Avoid Maneuvers Avoidance and Return to orig. Track 1.Conflict 4 Flights 32 Conflicts min. lateral Separation >500 ft Braunschweig Final Conflict Slide 7

8 HD-Camera Results from S&A Trials full view Slide 8

9 HD-Camera Results from S&A Trials - zoom Slide 9

10 HD-Camera Results from S&A Trials Target Recognition Slide 10

11 Reliability UAS in controlled airspace UA all have Electronic Flight Control Systems (EFCS) No EFCS reliability requirements in catastrophic faults per flight hour: Pilot commercial aircraft 10-9 / h military aircraft 10-7 / h Development of EFCS is very expensive due to reliability requirements. UAS will have to have similar reliabilities if they want to share civil airspace. A Sense and Avoid System that guarantees ELOS would have to be put in front of EFCS What is the required reliability going to be? Is that reliability achievable and/or affordable for civil applications? Sense & Avoid 10 -? / h??? commands traffic avoidance maneuvers EFCS 10-7 / h flies the aircaft Slide 11

12 Urban Environments The necessity of low altitude flight Flying VTOL UAVs in urban environments is of high interest, e.g. for surveillance, reconnaissance and data base building missions Small Fixed-Wing UAVs in urban environments will have to be able to take-off and land in difficult environments Test site Rosenkrug Slide 12

13 Stereo-Based Map Building (In-Flight) Measuring Object Distances Find Occupied and Free Areas (3D grid) Calculate 3-D Object Shapes Build or update environment map. Slide 13

14 Mapping Flight Test Results: Video Slide 14

15 Vision based GPS Loss Compensation Estimation of attitude and position based on arbitrary textures Automatic generation of new markers during movements Feature Tracker Suitable for hover and regular flight Slide 15

16 Slide 16

17 Autonomous Gate Crossing Gate position is only pre-defined by rough coordinates Detect gate flags Estimating geodetic gate position Estimate Navigation and Camera Misalignment during Flight Generate Waypoints Precise Flight through Gates Challenge: Navigation Accuracy of Small UAS is Unsufficient!. Slide 17

18 Slide 18

19 Automatic Mission Planning - What do we need? Offline path planning before Take-Off Obstacle recognition using a collision avoidance sensor Online re-planning of the flight path planned trajectory X unknown obstacle re-planned trajectory Slide 19

20 3D Path Planner Graph-based Path Search, Spline-based Smoothing maximum height 25m 780m x 400m area 278 QRM samples Slide 20

21 3D Trajectory Generation Graph-based Path Search, Spline-based Smoothing B Detected obstacle polygon Agent B B New, smoothed path FOV New path on search graph A A A A Online 3D Path Planning > Slide Folie 21 Joao G. Furlan Rocha > Abt. Unbemannte Luftfahrzeuge > Institut für Flugsystemtechnik

22 3D Trajectory Generation Berlin, Potsdamer Platz Polygons loaded in sec World Size 496m*548m*122.4m (WxLxH) QRM-sampling Roadmap built 25.6 sec Mission planned in sec Slide 22

23 Berlin, Mitte 3D Trajectory Generation (cont) World Model loaded in sec. Quasi random Halton sampling for [x=1748,y=1396,z=125.2] Roadmap build time sec Path length: m Waypoints: 138 Roadmap path planning in sec Spline-based smoothing in sec Mission planned in sec Slide 23

24 Research Challenges Safe Use of the Flight Environment No Develop effective and affordable sensor systems for flight control Pilot purposes Sense & Avoid of noncooperative aircraft Radar, Camera, Lidar Obstacle detection close to the ground Navigation without GPS Urban environments, Indoor flight Higher navigation accuracy for the flight control system Increase autonomy and safety for operations during data link loss or other emergencies Generate safe flight trajectories in difficult environments Enable the Unmanned Aircraft to make its own decisions Find ways to prove the stability and correctness of the intelligent software algorithms that allow the above Slide 24

25 What system reliability is required for civil applications? Use Case: Forest-Fire Detection Can a UAS be a fire hazard? Electric Aircraft might short circuit in a crash. Piston-powered aircraft have hot exhaust pipes. Turbine-powered aircraft can easily start fires. What is the trade-off? Fires successfully detected vs fires caused? How reliable does a Fire Detecetion UAS need to be? Slide 25

26 Reliability - Small UAS in civil security No What are the reliability requirements of small UAS in civil applications? Pilot (examples fire detection or border surveillance) Assumption: equal to Category II UAS of German Armed Forces max. kinetic energy < 50 kj 10-4 / h max. kinetic energy < 5 MJ 10-5 / h max. kinetic energy > 5 MJ 10-6 / h An affordable UAS has a weight of 10 kg, a max speed of 150 km/h required reliability 10-4 / h One crash in h One crash in 3 years of operation (12 h / d). Is that good enough? How expensive will it be? Slide 26

27 Research Challenge High Reliability at Low Cost Advanced Micro-Avionics No Pilot redundancy architectures (processors, sensors and actuators) based on COTS components for affordability small and light for affordable airframes Affordable Software development process Code needs to be reliable according to aviation standards Tool-based Software-Development Adapt development processes to miniature avionics Reliable and Safe Airframe Design More reliable components (engines, motors, actuators) Develop airframes with smart and safe flight termination systems Slide 27

28 Summary - Research Challenges for better Civilian UAS No Develop effective and affordable sensor systems for flight control Pilot purposes to increase situational awareness Increase autonomy and safety for operations and be able to prove it Develop advanced redundant and reliable Micro-Avionics Create an affordable and safe software development process for safety critical aspects of UAV flight Invest in reliable and safe airframe design to minimize damage to people in emergencies Slide 28