We are using custom built hydrophones provided by LAB-Core Systems, which are mounted to wings below the hull in an equilateral triangle. The hydrophone outputs are fed into a custom built circuit board housing three dpPIC33FJ12 digital signals processors (DSPs) that are then sampled through a central general-purpose PIC18F26K20 microcontroller.
In the course of developing the Pacific Nautilus AUVs we have published a number of white papers to document the development of the hydrophone system. The Hydrophones Mathematical Model, Hydrophone Sampling and Pyramid Search paper was developed in cooperation with Pacific Nautilus by Dr. Colin Bradbury who is a respected member of our team and a trusted advisor. Additionally, Dr. Bradbury developed a program to mathematically simulate the signal detection and bearing calculation task. The Hydrophones Model Program was used to determine the most efficient configuration for the hydrophone array and to investigate various bearing analysis algorithms.
The reason for taking on the challenge of creating a new pressure sensor for this year's competition was two fold. We had tight budget constraints to consider, and we needed something smaller to continue our objective of using the vehicle's laminar flow characteristics.
Our budget did not allow us to purchase a water pressure sensor outright so we decided to invest some time into exploring ways of using a much less expensive gas pressure sensor (GPS) to produce usable data. GPS cost about ten times less than devices specifically designed to measure fluid pressure. The challenge was to create a mechanism that could produce a close-to linear correspondence between the vehicle's depth and the output of the GPS. Three designs seemed to be promising.
The first was a cylinder/piston design made with a plastic syringe. After much testing with air pressure simulating the vehicle at different depths, the design seemed to work. All that was left a final test in water... it failed miserably. The water seemed to make the inner surface sticky rendering the piston immovable.
The next two designs had much more promise. One was a rubber diaphragm stretched over a hard plastic housing attached to the sensor with plastic tubing. The second was a rubber bulb attached directly to the pressure sensor. Both were about the same size.
After running both mechanisms through the same series of tests, it was determined that both produced very similar results. In the end, the diaphragm design was able to be made much smaller than the prototypes and it was settled on as the mechanism to be used.
The gyroscope we're using is the EVAL-ADXRS610Z, which is a yaw rate gyroscope with a bandwidth of 20Hz. The gyro outputs analog data corresponding to the yaw from the orientation of the circuit board that it is connected to, in our case the half-brain (Microchip PIC18F2525).
Through various testing simulations we were able to output data by rotating the half-brain in planned degrees of rotation. We then translated the analog data to a 10 bit decimal by dividing it by 1023. We then graphed the output data and made observations about whether it made sense to our testing procedures.
We noticed that the data was dominated by ground noise and also made predictions of the turn angles from the data. To justify our predictions we derived a formula for the turn angles, taking the sum of 8 periods of 8 measurements, 64 samples total. Then dividing the floor formula by 2 would decrease the noise. That gives an average rate of turn in the range of 0 to 511 with straight being a reading of about 256 (plus or minus 8), subtract 264 to get a positive number for turning right and a negative for turning left and proving our predictions to be accurate towards the simulated tests.