Justin Poh
  • Welcome
  • Publications & Presentations
  • Resume
  • Undergrad Work
    • Course Projects >
      • Mechanical Engineering/Material Science >
        • Design Nature, Fall 2012
        • Transport Phenomena, Fall 2014
        • Mechanical Design, Fall 2014
        • MechSolids, Spring 2014
        • Dynamics, Fall 2013
      • Robotics >
        • Principles of Engineering, Fall 2013
        • Fundamentals of Robotics, Fall 2014
      • Product Design & Development >
        • NEADS System Design, Fall 2015
        • UOCD, Spring 2014
        • Engineering for Humanity, Spring 2013
      • Electrical/Software Engineering >
        • Software Design, Fall 2013
        • Real World Measurements, Spring 2013
        • Modeling & Control, Fall 2012
      • Data Science & Analysis >
        • Analyzing Gait Data, Spring 2015
        • Crowd Flow Modeling, Spring 2015
    • Undergrad Research >
      • Gator Research, Spring 2016
      • Gator Research, Fall 2015
      • Robotic Tuna Research, Fall 2014
      • Robotic Tuna Research, Summer 2014

Robotic Tuna Research
Fall 2014

There were two goals of research on the robotic tuna during the fall semester:
  • Transition the fish from being reliant on an umbilical chord to control it to having the computation on board
  • Developing the structured light system for obstacle detection under water
 

1. Transitioning to Computation on Board

To transition the fish to having computation on board, we chose to use the NI myRIO, a control board that includes  both an FPGA layer as well as a real-time layer. Both layers are programmed through LabVIEW.


The brain structure for the robotic fish is an adaptation of the Robot-In-A-Box brain architecture that is used by numerous projects in the Olin Intelligent Vehicles Laboratory at Olin College. In essence, this brain architecture is the result of combining the Sense-Think-Act paradigm as well as the Hindbrain-Midbrain-Forebrain structure of human brains.
The following is the current version of the brain for the robotic fish:
 
2. Developing the Structure Light System for Obstacle Detection

Because traditional methods of obstacle detection (e.g. infrared sensors) no longer work under water, we needed to develop a new way to detect obstacles under water as well as seek out walls to implement a wall-following behavior. Thus, we decided to use a detection method known as structured light. In essence, a laser casts a horizontal laser line across the plane of view of the camera. If an object is present, the laser line will be divided into segments of different heights. Using the heights of the line segments and some computation, the distance between the camera and the object can be calculated. 


A video of the current version of this system is shown in the video below
Last Updated: 30 December 2024
  • Welcome
  • Publications & Presentations
  • Resume
  • Undergrad Work
    • Course Projects >
      • Mechanical Engineering/Material Science >
        • Design Nature, Fall 2012
        • Transport Phenomena, Fall 2014
        • Mechanical Design, Fall 2014
        • MechSolids, Spring 2014
        • Dynamics, Fall 2013
      • Robotics >
        • Principles of Engineering, Fall 2013
        • Fundamentals of Robotics, Fall 2014
      • Product Design & Development >
        • NEADS System Design, Fall 2015
        • UOCD, Spring 2014
        • Engineering for Humanity, Spring 2013
      • Electrical/Software Engineering >
        • Software Design, Fall 2013
        • Real World Measurements, Spring 2013
        • Modeling & Control, Fall 2012
      • Data Science & Analysis >
        • Analyzing Gait Data, Spring 2015
        • Crowd Flow Modeling, Spring 2015
    • Undergrad Research >
      • Gator Research, Spring 2016
      • Gator Research, Fall 2015
      • Robotic Tuna Research, Fall 2014
      • Robotic Tuna Research, Summer 2014