MIT Computer Science & Artificial Intelligence Laboratory MIT Dept. of Mechanical Engineering Cooperative Navigation for Groups of Autonomous Underwater Vehicles ASAP Hot Wash Meeting – November 2006

MIT Computer Science & Artificial Intelligence Laboratory MIT Dept. of Mechanical Engineering What navigation information do we have? GPS: Only for surface(d) vehicles Dead-reckoning: Compass+speed est. → Error: 10% dist. traveled Doppler Velocity Logger → Error: 1% dist. traveled → Distance < 200 m to bottom or surface Inertial Navigation System → Error: 0.2% dist. traveled → Expensive ($100,000) Navigation error grows without bound for DR, DVL and INS !

MIT Computer Science & Artificial Intelligence Laboratory MIT Dept. of Mechanical Engineering How about Sharing Navigation Information Other vehicles may know better where they are and share this information Examples: Solar AUV on surface Surfaced glider AUV with more sophisticated INS

MIT Computer Science & Artificial Intelligence Laboratory MIT Dept. of Mechanical Engineering Requirements for Cooperative Navigation Acoustic modem (WHOI): –Maximum range: 200 m - 4 km –Maximum data rate: 3 bytes/s - 1 kByte/s –Power consumption: 100 mW in receive mode Precise clock –Synchronized at surface to GPS clock –Drift O(Milliseconds per hour) –Enable one way ranging to transmitting vehicles Bandwidth for transmitted information –Position, position uncertainty, (heading, pitch, speed) –Necessary information is contained in most CCL packages –Vehicle-to-vehicle range for free

MIT Computer Science & Artificial Intelligence Laboratory MIT Dept. of Mechanical Engineering Cooperative Navigation Research at MIT ASAP/MB06 experiment in Monterey, CA, August 2006: Kayak to AUV Boston: (In cooperation with Bluefin) Kayak to KayakKayak to Glider Alexander Bahr, John J. Leonard, Cooperative Localization for Autonomous Underwater Vehicles, In Proceedings of the 10th International Symposium on Experimental Robotics (ISER), Rio de Janeiro, Brasil, July 2006 Publications:

MIT Computer Science & Artificial Intelligence Laboratory MIT Dept. of Mechanical Engineering Joint Kayak-Glider Experiment at MB06

MIT Computer Science & Artificial Intelligence Laboratory MIT Dept. of Mechanical Engineering Kayak to Glider Ranges

MIT Computer Science & Artificial Intelligence Laboratory MIT Dept. of Mechanical Engineering Upcoming Theory and Algorithms –Development of new Cooperative Navigation algorithms –Comparing performance by post processing collected data sets –Defining the minimal amount of necessary information which needs to be transferred Experiments –AUVs: Kayak to AUV in real-time, AUV to AUV (first post-processing, then real-time) –Glider: Dedicated Cooperative Navigation experiment with gliders Kayak to glider, glider to glider (real-time, post-processing)

MIT Computer Science & Artificial Intelligence Laboratory MIT Dept. of Mechanical Engineering Autonomous CTD casts Kayak outfitted with CTD on winch (70 m cable, 10 min/station) Predetermined pattern (Iuliu Vasilescu) Autonomous gradient following (Don Eickstedt)