Team Kanaloa 1 of 7

# University of Hawai’i at Manoa: Team Kanaloa

Peter Joseph Agcanas, Raymond Andrade, Paul Baessler, Bradley Beeksma, Michael Borunsinski, Kekoa Data, Blaine Furman, Hunter Garrett, Dominic Gaspar, Danny Hong, Kai Jones, Serena Kobayashi, Cheyenne Marie Langamin, Yong Cong Li, Charmaine Lum, Lisa Mahan, Curran Meek, Kealoha Moody, Kai Outlaw-Spruell, Jordan Romanelli, Dane Sobol, Dr. Zhuoyuan Song, Daniel Truong, Dr. A Zachary Trimble, Allison Wong, Brennan Yamamoto

Abstract— Team Kanaloa is part of the Renewable Energy, Industrial Automation, and Precision Engineering (RIP) research group aimed towards the advancement of unmanned systems. Team Kanaloa is developing an autonomous surface vehicle (ASV) to compete in the 2018 Maritime RobotX Challenge held by Association for Unmanned Vehicle Systems International (AUVSI). The ASV will execute two tasks: Scan the Code and Identifying Symbols and Dock to demonstrate fundamental autonomy. The ASV compromises of a holonomic propulsion system, flexible wireless system, a modular mounting rack for hardware and sensors, 50V power system.

### B. Identifying Symbols and Dock

Completion of Identifying symbols and dock starts by identifying the shape located at the dock using a Regional Convolutional Neural Network (R-CNN) available on MATLAB. The R-CNN also identifies the location of the shape in the picture frame. Once the shape and location are identified, the WAM-V utilize the HSV from Scan the Code to identify the shape’s color. Then, the WAM-V detects the range from the dock using a LiDAR and the waypoint navigation code, the WAM-V will dock in the correct bay.

## I. INTRODUCTION

## III. VEHICLE DESIGN

Team Kanaloa, from the University of Hawai’i at Manoa, is a multidisciplinary group of, primarily, undergraduate students who aim to research and advance autonomous maritime systems. Team Kanaloa is developing the WAM- V to compete in the 2018 Maritime RobotX Challenge to demonstrate the student’s capabilities of developing an ASV. During the off season of the Maritime RobotX Challenge, autonomous capabilities of the Wave Adaptive Modular-Vehicle (WAM-V) is developed and utilized for side research projects.

This section describes the changes made to the mechanical, hardware, and software that was implemented. Descriptions of prior iterations, component choices, design approaches, and results shall be included.

### A. Mechanical System

Team Kanaloa made several mechanical modifications and enhancements to its WAM-V, which are shown in Figure 2.

## II. DESIGN STRATEGY

### A. Scan the Code

Completion of Scan the Code task starts using our developed Hue Saturation Value (HSV) threshold that classifies red, green, and blue. The WAM-V scans the pattern of the buoy twice, then reports the name and picture of the color to the user in order.

###### Figure 2: Team Kanaloa WAM-V

#### 1) Propulsion System

Team Kanaloa utilized four 55lb thrusters in a holonomic drive configuration at the 2016 RobotX Challenge. Holonomic drive provides the WAM-V with three degrees of motion and precise maneuverability. However, the disadvantage of the holonomic configuration lied in the fixed positional angles of the thrusters. This was inefficient for fully moving forward or backwards compared to a normal drive train. Another issue became apparent when the ocean currents at a sea state level of 2 was able to easily push the WAM-V around during systems testing at Sand Island. Two solution strategies were developed to mitigate

###### Figure 1: HSV to identify the color pattern.