Development of Control for Multiple Autonomous Surface Vehicles (ASV) Co-Leaders: Forrest Walen, Justyn Sterritt Team Members: Andrea Dargie, Paul Willis,

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Development of Control for Multiple Autonomous Surface Vehicles (ASV) Co-Leaders: Forrest Walen, Justyn Sterritt Team Members: Andrea Dargie, Paul Willis, Phil Goff, Lucas Davies, Ben Novak Advisor: Dr. May-Win Thein Graduate Advisors: Andrew D’Amore, Damian Manda ASV Systems and Control ASV subsystem requires integration of multiple fields of engineering (e.g., mechanical, electrical, and software). Inherent issues in integration involve system and subsystem communication and control. MOOS-IvP software platforms (incorporating ROS) are used to integrate multiple vehicle sensors and actuators, along with user-defined command inputs. Advanced modeling and control techniques are to be implemented to ensure performance, robustness, and reliability for autonomous obstacle avoidance and required path planning. MOOSDB iGP9/iGPS iMOOSArduino iSonar pHelmIvP pRecordSwath pShare uFldNodeBroker pSurveyPath pMarinePID pHostInfo pLogger Depth, Swath Width Start/ Stop Log Depth, Swath Width, Posn, Heading Min Swaths Posn, Velocity, Attitude Min Swaths, Op. Boundary Waypoints Rudder, Throttle IP Address Shore Station Info pShare Config All Info ASV Posn, Status Shore Command Position, Heading, Waypoints, Depth, Obstacles Desired Heading, Speed Start/Stop Log Rudder, Throttle Desired Hdg, Speed Current Hdg, Speed Monitoring and Logging Sensor Interfaces Survey Path Planning Autonomy and Control Supplied Application Custom Application iLidar Obstacles Position Fit Commercial Platform with Autonomous Control System 58” length 15 lbs Maximum speed 40 mph Brushless electric motor for propulsion Servo-powered rudder Autonomous Control System Battery Pack: Outputs 5 V. Powers Arduino and BeagleBone 1100 Kv Brushless motor 120A Water- cooled ESC V 3200mAh battery packs to run the motor and servo BeagleBone Black: Used as the brain of autonomy. Runs MOOS-IvP Servo used to steer rudder. Arduino Mega 2560: Used to control motor and servo Autonomy Control Program: MOOS-IvP MOOSDB: Mission Orientated Operating Suite. MOOS stores information related to its operating mission and coordinates communication between sensors and other processes. IvP Helm: Interval Programming Helm. The IvP helm is able to take information from MOOS and make control decisions for the boat. Complex autonomous scenarios can be developed from package supplied or custom developed behaviors LIDAR: Distance sensing by analyzing the response of an object to a laser. The LIDAR module is a rotating head with laser and image sensor with an onboard microprocessor to compute angle and distance data of objects via serial. The beaglebone runs a program to interpret the serial stream and send messages to MOOS for obstacle recognition. Stages of Autonomy First Stage Autonomy: Basic point to point navigation using GPS navigation integrated with an IMU to increase the reliability of the navigation system. Second Stage Autonomy: Second stage autonomy involves pairing point to point navigation with obstacle avoidance, thereby creating a self sufficient navigation algorithm to serve as a platform for more complex tasks. Third Stage Autonomy: The third stage of autonomous control is to allow for a leader/lagger formation to be implemented on one of these platforms, specifically the ability for an autonomous vehicle to follow a sister vehicle with the intention of completing a more complex task in tandem. Ɵ d Second Stage Autonomy Schematic Sensors GPS: Adafruit Ultimate GPS Breakout used for point to point navigation. degrees-of-freedom-razor-imu-ahrs-compatible-large.jpg XV11Teardown/TheGoodStuffMasked.jpg LIDAR: Light detection and ranging system. Used Neato Robotics XV-11 LIDAR for proof of concept object detection programming. Razor IMU: This IMU is used to correct the short term velocity and acceleration being used by MOOS for predictive navigation. ASV Tasks Search and rescue operations, a swarm could cover more ground without endangering more human lives. Ocean mapping, eliminates human error and cost of human labor in large scale ocean mapping projects. A swarm could also work together to form a large scale passive barrier to protect the naval borders of nations around the world. In general this vehicle is meant to perform tasks that have been deemed either too dangerous or too inefficient for human involvement.