An Evaluation of Occupancy Sensing Methods for Autonomous Underwater Vehicle Docking

Abstract

Docking stations play a critical role in the long-term deployment of autonomous underwater vehicles (AUVs) by automating a range of costly tasks [4], [5]. One requirement of a functional station is an occupancy sensor system capable of detecting when the AUV is correctly oriented to initiate docking. A majority of occupancy sensing approaches presented in academic literature either employ specialized equipment, require a particular form factor to implement, or lack sufficient technical detail to replicate. To address these shortcomings, this report presents the implementation and evaluation of various occupancy sensing methods using inexpensive, commercially available components conformable to many AUV and docking station form factors. First, it was determined that contact-based sensing, implemented with a limit switch, successfully confirmed a critical segment of the AUV was in place to initiate docking. If precautions are implemented to mitigate the risk of false positives, contact-based sensing has a strong potential to reliably measure AUV occupancy. Second, a commercially available radio frequency identification (RFID) reader was found to successfully propagate RFID signals through barriers of air, tap water, and salt water. This demonstrates its potential for use in both fresh and saltwater environments. However, the serial connection to the reader was found to fail in a chlorinated pool, which presents operational issues in certain conductive mediums. Third, a commercially available inductive module was found to successfully couple through barriers of air and tap water, demonstrating its potential to measure AUV occupancy in a freshwater environment by monitoring the current circulating the transmitter. However, coupling was not observed through chlorinated pool water, indicating the module is prone to attenuation in more conductive, electrolyte mediums. Lastly, it was found that applying a simple high-pass filtering algorithm to the accelerometer output of an inertial measurement unit (IMU) was highly effective in characterizing collisions between the AUV and docking station. Moreover, collision detection may be a viable approach to occupancy detection if additional functionality is implemented to distinguish AUV and environmental collisions.