Design and Development of an Autonomous Surface Watercraft Sponsor: Dr. D. Dunlap Advisor: Dr. J. Clark Instructors: Dr. N. Gupta, Dr. C. Shih Team 18: Donald Gahres, Kyle Ladyko, Samuel Nauditt, Teresa Patterson Presenters: Donald Gahres, Kyle Ladyko 30 March 2017

Competition Recap Annual Roboboat competition has boats autonomously navigate through a lake course Competition Challenges: Weight/Thrust Measurement Basic Navigation Obstacle Avoidance Automated Docking Interoperability Acoustic Beacon/Pinger Location Return to Dock Sam Presenter:

Real World Applications of Competition Tasks Types of Mines Contact Mines Influence/Acoustic Mines Buoy Navigation Mimics field of contact mines Acoustic Pinger & Interoperability Deployment of mine-hunting sonar systems AN/AQS-20A AMNS 2017 Predicted Drone Task Northrop Grumman ALMDS Presenter:

Project Scope Goal Statement: Create a lightweight surface vehicle capable of maneuvering a course autonomously with a focus on obstacle avoidance, waypoint navigation, and color and shape recognition while remaining versatile for later subsystems to be added. Insert competition layout gfraphic and colored bullets Presenter:

Recap: Hull, Electronics, and Weight Access hatches installed 8020 platform, threaded rod, and plates installed for sturdy pontoon connection Camera housing installed Electronics housing installed Thrusters installed Electronics Clean layout of components. Large space allows for integration of future subsystems Weight Current weight: 65 lbs. Estimated final weight: 85 lbs. Design can be iterated so that a second year team can aim for the bonus points offered by the competition for a watercraft weighing less than 70 lbs. Presenter:

Recap: Testing Preparation and Results Construction of components for course simulations Electronics dry tested for successful integration from prototype Procedures laid out for necessary tests to ensure efficiency Mobile testing setup organized Test Results Accomplishments Weight/Thrust measurement Manual control operable Basic autonomous navigation Robustness of design Weaknesses identified for immediate address Test Buoy Height Field of view Presenter:

Mapping and Planning: Vector Field Histogram Maps robot position and obstacles to NxN grid Calculates robot's path based on obstacle density and target location RTK-GPS and LIDAR integrated, magnetometer and thruster control functions in process Presenter:

Why the Switch? Previously planned to utilize SLAM for obstacle avoidance challenge Discussion with sponsor led to decision to change method to Vector Field Histogram Computational cost is much lower No need for separate path planning algorithm Presenter:

Challenges and Future Addresses Tuning VFH threshold and constants during testing for optimal results Group availability for testing Future Size constraints to keep in mind for drone task for second year Continue testing autonomy Mobility of testing setup Presenter:

Spring 2017 Gantt Chart Presenter:

Testing Status Testing Status Test Date - Completed   Test Date Weight Measurement 17 FEB Thrust Measurement 19 FEB Buoyancy Structural/Watertight Integrity Object Detection using Camera MONTHLY Autonomously Navigate Channel Markers Autonomous Buoy Navigation 01 APR Remote Control BI-WEEKLY GPS and LIDAR Dry Test DAILY Object Avoidance Coding Daily - Completed - Accomplished, but will undergo further tests Presenter: 11

Conclusion Completed Items Immediate Plans Future Plans Final modifications made on boat Organized layout of electrical components Weight/Thrust measurement Basic navigation VFH algorithm written Immediate Plans Implementation of VFH Testing VFH algorithm LIDAR installation Future Plans Test and debug autonomous obstacle avoidance Presenter:

Questions? Sam Presenter: