Transcript Artificial Intelligence Laboratory MIT Dept. of Mechanical Engineering

Cooperative Navigation for Groups of
Autonomous Underwater Vehicles
ASAP Hot Wash Meeting – November 2006
MIT Dept. of Mechanical Engineering
MIT Computer Science & Artificial Intelligence Laboratory
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 Dept. of Mechanical Engineering
MIT Computer Science & Artificial Intelligence Laboratory
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 Dept. of Mechanical Engineering
MIT Computer Science & Artificial Intelligence Laboratory
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 Dept. of Mechanical Engineering
MIT Computer Science & Artificial Intelligence Laboratory
Cooperative Navigation Research at MIT
• ASAP/MB06 experiment in Monterey, CA, August 2006:
Kayak to AUV
Kayak to Kayak
Kayak to Glider
• Boston:
(In cooperation
with Bluefin)
• Publications:
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
MIT Dept. of Mechanical Engineering
MIT Computer Science & Artificial Intelligence Laboratory
Joint Kayak-Glider Experiment at MB06
MIT Dept. of Mechanical Engineering
MIT Computer Science & Artificial Intelligence Laboratory
Kayak to Glider Ranges
MIT Dept. of Mechanical Engineering
MIT Computer Science & Artificial Intelligence Laboratory
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 Dept. of Mechanical Engineering
MIT Computer Science & Artificial Intelligence Laboratory
Autonomous CTD casts
Kayak outfitted with CTD on winch (70 m cable, 10 min/station)
• Predetermined pattern (Iuliu Vasilescu)
• Autonomous gradient following (Don Eickstedt)
MIT Dept. of Mechanical Engineering
MIT Computer Science & Artificial Intelligence Laboratory