《卫星工程》英文版 18 autonomy lec

Spacecraft Autonomy Seung H Chung Massachusetts 16.851 Institute of Satellite Engineering Technology Fd‖2003

16.851 Satellite Engineering Fall 2003 Massachusetts Institute of Technology Spacecraft Autonomy Seung H. Chung

hy autonomy Failures Anomalies Communication Coordination New horizons Europ/Robe courtesY Apollo 13 Quintuple fault (three shorts, tank- line and pressure jacket burst, panel es o ofi) Mars polar ander Mars Outpost Massachusetts Institute of Technology

2 Massachusetts Institute of Technology Why Autonomy? • Failures • Anomalies • Communication • Coordination courtesy of NASA JPL New Horizons Europa Probe Courtesy of the Johns Hopkins University courtesy of NASA Apollo 13 Quintuple fault (three shorts, tank￾line and pressure jacket burst, panel flies off). Mars Polar Lander courtesy of NASA JPL Mars Outpost courtesy of NASA JPL Applied Physics Laboratory. Used with permission

Autonomy Technologies Fault Detection, Isolation and Recovery Planning Scheduling Intelligent Data Understanding Path Planning Gradient method Mixed integer linear programming(Prof John How) Graph search(Prof Brian Williams) Localization Mapping Concurrent mapping and localization(Prof John Leonard) Massachusetts Institute of Technology

3 Massachusetts Institute of Technology Autonomy Technologies • Fault Detection, Isolation and Recovery • Planning & Scheduling • Intelligent Data Understanding • Path Planning – Gradient method – Mixed integer linear programming (Prof John How) – Graph search (Prof Brian Williams) • Localization & Mapping – Concurrent mapping and localization (Prof John Leonard)

Why Fault Detection Isolation Recovery (FDIR)? Improve the likelihood of mission success by minimizing the downtime Increase productivity Prevent loss of opportunities Reduce safety risk For manned missions, longer system downtime implies higher risk to the astronauts Massachusetts Institute of Technology

4 Massachusetts Institute of Technology Why Fault Detection Isolation & Recovery (FDIR)? • Improve the likelihood of mission success by minimizing the downtime. – Increase productivity – Prevent loss of opportunities – Reduce safety risk • For manned missions, longer system downtime implies higher risk to the astronauts

FDIR Techniques If-then-else Hard coded set of fdir statements Rule-based Set of rules written by the engineers Fires a rule (i.e. executes a rule) when the rule is satisfied EXample #24(D>1A)And(Shunt D> 6A)for 10 sec, then Try Sec Bus Reg_ Off #27 (Red Battery Charger is ON) for 5 sec, then rule(28, 29 )stop The core software is reusable Engineers must enumerate all possible faults and combinations thereof along with the corresponding recovery methods Verifying the validity of the rules is difficult Massachusetts Institute of Technology

5 Massachusetts Institute of Technology FDIR Techniques • If-then-else – Hard coded set of FDIR statements • Rule-based – Set of rules written by the engineers – Fires a rule (i.e. executes a rule) when the rule is satisfied – Example • #24 (ID > 1A) And (Ishunt_D > 6A) for 10 sec, then Try_Sec_Bus_Reg_Off. • #27 (Red Battery Charger is ON) for 5 sec, then rule (28,29) stop. – The core software is reusable. – Engineers must enumerate all possible faults and combinations thereof along with the corresponding recovery methods. – Verifying the validity of the rules is difficult

Model-based FDIR Technique Engineers model the behavior of the system(i.e components) Computer detects/isolates/recovers faults by reasoning on the model of the system Both the model and the model-based FDIR system can be reused Problem too difficult for a computer? I 323 Model-based Observation FDIR Command System Massachusetts Institute of Technology

6 Massachusetts Institute of Technology Model-based FDIR Technique • Engineers model the behavior of the system (i.e. components). • Computer detects/isolates/recovers faults by reasoning on the model of the system. • Both the model and the model-based FDIR system can be reused. • Problem too difficult for a computer? Model-based FDIR System Observation Command

Planning Scheduling Planning Given: Set of actions a system can perform and the associated requirements and effects of the actions Current state Desired goal state Objective: Compute a sequence of actions that achieves the desired goal state Scheduling Given: Set of tasks to execute and the associated constraints (i.e. time, resource, .. Objective: Compute the proper order of the tasks that satisfies the constraints 7 Massachusetts Institute of Technology

7 Massachusetts Institute of Technology Planning & Scheduling • Planning – Given: • Set of actions a system can perform and the associated requirements and effects of the actions • Current state • Desired goal state – Objective: Compute a sequence of actions that achieves the desired goal state. • Scheduling – Given: Set of tasks to execute and the associated constraints (i.e. time, resource, …) – Objective: Compute the proper order of the tasks that satisfies the constraints

Planning example Goal: Take an image of Alpha centauri Plan 1. Compute current position and attitude 2. Compute the necessary position and attitude for Alpha Centauri to be in view 3. Initialize and warm-up the imaging system 4. Change the position and point toward Alpha Centauri 5. Open the shutter 6. Take image 8 Massachusetts Institute of Technology

8 Massachusetts Institute of Technology Planning Example • Goal: Take an image of Alpha Centauri • Plan: 1. Compute current position and attitude 2. Compute the necessary position and attitude for Alpha Centauri to be in view 3. Initialize and warm-up the imaging system 4. Change the position and point toward Alpha Centauri 5. Open the shutter 6. Take image

Why Planning& Scheduling Simplify spacecraft commanding Simplify mission operations work Enable timely replanning when necessary without communication time-delay issues Massachusetts Institute of Technology

9 Massachusetts Institute of Technology Why Planning & Scheduling? • Simplify spacecraft commanding. • Simplify mission operations work. • Enable timely replanning when necessary without communication time-delay issues

Intelligent Data Understanding What is it? Knowledge Discovery: Is this something new, something nteresting? Pattern Recognition: What are the identifiable characteristics? Classification and clustering Does this belong to some category of information? Why? The communication bandwidth does not allow transmission of all available data Serendipitous events Massachusetts Institute of Technology

10 Massachusetts Institute of Technology Intelligent Data Understanding • What is it? – Knowledge Discovery: Is this something new, something interesting? – Pattern Recognition: What are the identifiable characteristics? – Classification and Clustering: Does this belong to some category of information? • Why? – The communication bandwidth does not allow transmission of all available data. – Serendipitous events…