OBSTACLE AVOIDANCE

1. OBSTACLE AVOIDANCE APPLIED BEHAVIOR-BASED CONTROL IN AUVs NAME DATE TITLE Anton Gravestam 12 15 2008 OBSTACLE AVOIDANCE

2. Overall Control Strategy Mission – Planning and Execution Behavior-Based Control Obstacle Avoidance Priority Tuning Present and Future References OUTLINE

3. Control decomposition into functional layers with different temporal requirements and levels of abstraction. Degree of autonomy determined by number of layers under vehicle control. Decoupling of high level control functionality from specific vehicle platform Behavior based control at the core of extendable reactive autonomy. Planning Deliberative layer Mission plan Behavior-basedcontrol Reactive layer Low-levelcontrol layer PID-control Control signals Actuators OVERALL CONTROL STRATEGY Reference values(heading, speed etc.)

4. MISSION - PLANNING AND EXECUTION • Missions consist of Actions: • Sequential discrete events • Well-known transition models • For example: Transport, MineSearch, Docking • Actions consist of Behaviors: • Parallel continuous control functions • Activated during runtime • Example: AvoidObstacle, GotoWaypoint(W), GetGPS-position Transport MineSearch Transport Docking 1 2 3 4 Docking AvoidObstacle AvoidObstacle AvoidObstacle FollowSeaBed GetGPS-position GetGPS-position GotoWaypoint(W1) GotoWaypoint(W2) FollowSearchPattern

5. Sensordata Behavior Priority p1 Arbitration Sensordata Behavior p2 p3 Sensordata Behavior BEHAVIOR-BASED CONTROL • Each behavior can voice its opinion on best course of action • Behavior responses as utility functions • An arbitration mechanism coordinates behaviors to maximize utility • Dynamic activation level and static priority determines behavior influence. • Reference values passed to low-level control system:roll, pitch, heading and speed in x, y, z. Referencevalue

6. WHY USE BEHAVIOR-BASED CONTROL? • Good approach for extendable autonomy functions.Capabilities can be added or improved by introducing new behaviors or by recombining existing. • Enable a vehicle to fulfill multiple requirements in parallel E.g. Avoiding obstacles while following waypoints. • Can accommodate for dynamic environments and unforeseen events unknown when planning • Widely used approach for autonomous mobile robotic control. • Overall vehicle behavior can be altered for different mission objectives by tuning behavior priorities. • Multiple behaviors concerned with the same thing can be present at the same time. Use high performance behaviors when safe, fall back to security behaviors when hazard risk is high.

7. BEHAVIOR-BASED CONTROL: EXAMPLE • 1: Track following:Follow track closely for best sonar coverage and platform stability. • 2: Waypoint navigation:Ensure that the overall goal of reaching the next waypoint is met • 3: Obstacle avoidance:Steer the vehicle clear of obstacles. Activation rises with hazard proximity. • 4: Avoid past:Influences the vehicle to favor a new path to avoid getting stuck in circular behaviors • 5: Emergency stop:Influences the vehicle cruising speed to decrease with obstacle proximity. Ultimately forces the vehicle to a full stop if to close. Activation level Hazard Risk Distance to Obstacle t

8. Occupancy grid Localization FLS IMU GPS DVL Sensor Stimuli Utility Function Response Obstacle Avoidance OBSTACLE AVOIDANCE • Behavior reacts to obstacle map (Occupancy grid) and vehicle position/orientation (Localization) • Response is formed as a utility function with minimums at directions of obstacles

9. Sensor Abstraction: Decouple high-level software from specific sensor hardware High level control functions (e.g. Obstacle avoidance) use high level sensor abstractions. Any number of different sensors can be used to enhance sensor data Occupancy grid Localization FLS IMU GPS DVL OBSTACLE AVOIDANCE

10. Occupancy Grid Short term 3D mapping of the surrounding environment used in real-time for obstacle avoidance. Memory enables reaction to obstacles no longer in field of view. Obstacle memory fades over time to accommodate for dynamic environments and drift in position estimate. Can be created from any type of proximity sensor. Use single sonar or multiples ones. OBSTACLE AVOIDANCE

11. OBSTACLE AVOIDANCE • One utility function for each degree of freedom represents a behaviors voice Behavior response from Track Follow behavior

12. OBSTACLE AVOIDANCE • Responses are weighted together and the maximum is chosen as the response to send to control system Behavior response from Track Follow behavior and Obstacle Avoidance weighted together

13. OBSTACLE AVOIDANCE • Increased activation of Obstacle avoidance as Obstacle approaches Behavior response from Track Follow behavior and Obstacle Avoidance weighted together

14. PRIORITY TUNING • Tuning individual behaviors priority gives vehicle different ”personalities” Bold Behavior Cautious Behavior Samples of path chosen with to sets of behavior priorities. To the left: High priority on obstacle avoidance. To the right: Higher priority on track following.

15. Middleware Node 1 subscribe Node 3 Topic 1 publish subscribe publish publish Topic 2 subscribe Node 2 PUTTING IT ALL TOGETHERUSING PUB/SUB MIDDLEWARE TECHNOLOGY • Open distributed architecture - flexible, transparent and scalable • Decentralized architecture, no central services/single point of failure • Asynchronous messaging with Quality of Services • Maps well to Behavior-Based Control • Enables isolation of time and safety critical functions

16. Operator controlled Autonomous Autonomous PRESENT AND FUTURE • Present: Autonomous control up to reactive layer • Future development should focus around intelligent autonomous replanning of missions to solve complicated hazard situations such as deep caves or under ice navigation Present Future