2020 Competition Vehicle

Design to Exceed

The 2019 boat, Wilson, was a good boat with a few problems. It was the lightest boat of the competition with an amazing thrust-to-weight ratio. So much so, (spoilers) it flipped in its last run of the competition.

Our 2020 design team focused on improving lessons learned from those problems, and creating a boat that would allow future teams the ability and space to compete in the competition. 

We have expanded the boat to a 30” X 50” size and incorporated the sensors into the final design. We have also tested the boat for buoyancy and stability to ensure that our boat functions in all situations.

2020 Boat Design Renderings

  • February Draft-Left
  • February Draft-Lid
  • February Draft-Right
  • Final Design-Front
  • Final Design-Back

Bringing It To Life

  • Courtney Constructing the Boat (1)
  • Courtney Constructing the Boat (2)
  • Structure of the Boat-Front
  • Structure of the Boat-Back
  • Float Test

Written by Toni Weaver, Seminole Coast Team Lead

The Power of Improvement

Marshall and Madison Testing Hardware on
The Hulk

In the summer of 2019, the Seminole Coast RoboBoat team’s power system allowed for the exposure of all electrical components inside their previous boat, Wilson.

The goal for this years project is to eliminate this major hazard and design a robust power system that is able to be handled safely, as well as be user friendly. The system will be capable of supporting multiple devices attached to it and properly powering them based on each component’s power requirements. It will also include active monitoring to provide constant feedback of voltage and current to a user.

Figure 1: Preliminary Final Design of Power Box

As seen in Figure 1 to the left, the power team designed a condense box that held all the conversion devices used to allow for the proper output of power for each device (Figure 2 below).

Figure 2: Power System Integration to the Entire System

Figures 3A and 3B below provide an internal overview to the layout of what exactly the inside of the power system looks like.

Figure 3A: Block Diagram of the First Layer
Figure 3B: Block Diagram of the Second Layer

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The system that has been provided here is by no means the system that was going to be brought to the 2019-2020 RoboBoat competition. Due to the COVID-19, the team was not able to build the final box that was going to have an acrylic casing and be much more pleasing to the eye to see. The team plans to continue this project to have a proper, robust power system for the next competition (2020-2021).

Written by Marshall Sowell; Lead of Power Team, Fundraising, and Marketing

Programming Through the Obstacles

Vehicle Used in Simulating a Map
Simulation of Mapping the School

To complete any task for RoboBoat we first needed to localize our vehicle in the environment. Without doing this, the vehicle would have no idea where it is. This turned out to be quite a difficult task as some of our sensors provided errors that we’ve never had any experience solving. This involved figuring out our IMU hardware and successfully integrating its data into the ROS environment. After much research we worked out a lot of the kinks with our IMU hardware and were one step closer to localizing the vehicle inside of the ROS coordinate frame.

Simulation Data

After we established where the vehicle understood where it was in the environment we had to give it a “set of eyes”. The “eyes” came in the form of our laser scanner, or LiDAR, this hardware allowed us to detect obstacles within our environment allowing the boat to see them. After we were detecting obstacles from the environment we could perform logic with them and determine suitable locations to set waypoints for vehicle. These waypoints would act as small navigational goals which enabled us to develop more complex path planning algorithms. These algorithms include simple algebra, and more complicated vector algebra.

PID Data on Plot Point
Mark and Brandon Testing the PID Controller

To provide a custom control system for the vehicle we decided on a PID controller. To implement this we decided to use C++ to write an algorithm that would drive the input errors to zero. Essentially, this took a very abrupt step function as an input given to the motors from the software modified them to have a smooth output. This output, generated by the controller, allows the vehicle to accelerate and decelerate smoothly. In real life, this allows the vehicle handle safely in the water without causing unstable, jerky motion.

Written by Mark Hartzog, Co-Lead of Software