We are proud to present Oogway, our advanced entry for RoboSub 2024.
This autonomous underwater vehicle (AUV) marks a major design evolution for our team, integrating new technologies and refining systems for enhanced performance. Oogway is built around a modular frame, supporting the independent integration of key components, with an accessible electrical stack for easier sensor expansion and integration. Its software includes cutting-edge computer vision integrated with all-new task planning and control systems allowing for precise object recognition and navigation. We’ve also implemented novel hardware to locate acoustic pings and an accurate marker dropper, enabling it to interact with its environment. Key to Oogway’s design is the seamless integration of its subsystems, enabling robust and reliable functionality. Each component was independently developed and tested, ensuring high performance and resilience under the demanding conditions of underwater missions. As it embarks on each task within the competition, Oogway demonstrates our team’s technical capabilities and our commitment to advancing the field of underwater robotics.
Come check out our Report!
Computer Science
Robot Controls, GUI, Computer Vision (CV), Sonar, and Task Planning are crucial for autonomous robotics. Robot controls manage movement and actions, while the GUI allows users to interact and monitor the robot. CV enables the robot to perceive and navigate its environment. Sonar sensors help with distance measurement and mapping, especially in low-visibility conditions. Task planning determines the optimal sequence of actions for achieving goals. Together, these systems enable robots to perform complex tasks autonomously in dynamic environments.
Controls
Our control system ensures precise and stable robot movement through a blend of feedforward and feedback control mechanisms. Feedforward control maximizes stability by counteracting persistent forces like buoyancy, while feedback control, implemented via Proportional-Integral-Derivative (PID) loops, ensures smooth navigation towards the target.
Further enhancing performance, the thrust allocator solves a quadratic programming problem using advanced numerical optimization techniques to determine the necessary force for each thruster, enabling the robot to follow the desired trajectory while minimizing energy usage. These forces are then transformed into pulse widths via a nonlinear mapping and pulse width modulation is employed to spin the thrusters. This sophisticated approach guarantees precise maneuverability across diverse environments and conditions.
GUI
Built on top of Foxglove Studio using the React Material UI library, the Duke Robotics GUI features a modular and modern design and allows us to easily monitor and control our AUV during pool tests. We can receive real-time updates on the status of our onboard computer, sensors, thrusters, and battery. We can observe the performance of the czontrols system and tune PID constants on-the-fly. We can use a joystick to control the robot directly. Individual panels are organized into layouts and easily deployed using a custom CLI. The GUI also supports replaying recorded ROS bag files for offline debugging and analysis.
CV
Detection
The computer vision (CV) system uses stereo and monovision inputs from both our DepthAI and USB cameras to locate items underwater to complete our underwater tasks. For simpler prediction tasks, we employ HSV filtering and contour matching to identify the buoy, path markers, and bin. For more intricate images encountered in the gate, torpedo, and octagon tasks, we utilize YOLO object detection models. Our enhanced CV pipeline seamlessly integrates these methodologies, dynamically adjusting to optimize detection speed and accuracy for various tasks.
Simulation
Our CV Simulation, built using Unity Perception, allows rapid generation of large-scale, labeled synthetic datasets for model training. Environment randomizations such as rotations and lighting variations contribute to a robust model that generalizes to a variety of diverse pool conditions. We also incorporated a realistic 3D model of the Woollett Aquatics Center to closely match this year’s competition environment.
Sonar
Our sonar system has been upgraded to enhance its reliability and provide alternate task completion methods. The upgraded sonar now effectively avoids false positives caused by acoustic reflections and can detect when the target object is missing. Low-intensity values are filtered out, and the DBSCAN algorithm is used to identify clusters in the image. Clusters are categorized as gate, buoy, and unknown. The clusters are used to identify the distance to the objects as well as their surface normal angles. The sonar can also perform long-range scans to get an overview of the AUV’s environment, filtering objects based on area and circularity and removing similar-sized neighboring clusters.
Task Planning
The task planning system serves as the robot’s top decision-maker, orchestrating its actions and responses to varying scenarios encountered during competition. It interfaces with all other systems, leveraging data from the robot’s perception capabilities and its current state to strategize and execute tasks efficiently by moving the robot or manipulating objects. Built upon a framework of coroutines, the system exhibits agility and responsiveness, swiftly adjusting to environmental changes and dynamically selecting the most optimal course of action at any given moment. The framework also facilitates streamlined development, allowing developers to assemble small building blocks into intricate tasks with ease. An automated system continuously publishes updates at every step, offering real-time insights into the system’s behavior and performance.
Electrical
The Electrical Stack Capsule houses and protects the robot’s electronics, ensuring efficient power distribution. Component mounts secure hardware like sensors and boards, providing stability. Actuators convert electrical signals into motion, driving the robot’s actions. The Full Model Assembly integrates these elements, allowing the robot to function seamlessly and perform tasks autonomously.
Full Electrical System
The electrical stack is the heart of the robot. Its primary responsibility is twofold — power all components, and ensure all data gets to the right places. This includes everything from communicating with all sensors, powering the robot computer, and even ensuring a network connection to the GUIs running on our landside computers.
This year, we rebuilt our electrical stack for two reasons. For one, we recognized a need for future expansion and overall optimization of component layout. And second, our capsule flooded.
Sensors
Oogway relies on many sensors to track both external and internal conditions.
Our primary sensors determine the robot’s state, that being it’s 6 degrees of freedom: x, y, z, roll, pitch, yaw. Our IMU, DVL, and pressure sensor are fused in software to provide an accurate state. The IMU and DVL both have their own direct UART serial connection to the PC whereas the pressure sensor is read through an Arduino and sent to the main ROS node over USB.
Oogway has two sonars onboard, both of which are connected to the computer’s USB.
We also have an internal voltage sensor to monitor the batter and adjust thruster efforts, a temperature sensor to monitor capsule heat, and a humidity sensor to detect water ingress. Each of these three internal sensors are read with an Arduino as well.
Cameras
Oogway has four cameras that we use for CV and monitoring. Two cameras are simple USB cameras rated for underwater and two are sophisticate stereoscopic cameras with internal processing. These cameras represent a significant demand for both our power and data systems.
We also utilize downward facing cameras to track path markers on the pool floor.
Thrusters + Marker Dropper
Oogway has 8 thrusters and it is electrical’s reponsibility for providing the layer of hardware abstraction used by controls. There are multiple challenges associated with the thrusters.
For one, the thrusters are located outside the capsule. With three 14AWG wires each, the thrusters introduce significant capsule penetration. Additionally, the ESCs mounted inside the capsule are physically large and come with significant wire mass when all power, data, and output wires are connected.
Additionally, the thrusters each require a precise PWM signal to be generated from our PC. Therefore, we run serial communication to an Arduino Nano Every that use an I2C multiplexer to initialize and control all thrusters. We have made corrective offsets to hardware defects that we measured on some ESCs.
Our marker dropper contains a servo that is connected to one of our Arduinos. Upon receiving the proper command over USB from ROS, we can individually drop both rounds from our dropper.
Mechanical
The Electrical Stack Capsule houses and protects the robot’s electronics, ensuring efficient power distribution. Component mounts secure hardware like sensors and boards, providing stability. Actuators convert electrical signals into motion, driving the robot’s actions. The Full Model Assembly integrates these elements, allowing the robot to function seamlessly and perform tasks autonomously.
Electrical Stack Capsule
Ensuring the watertightness of the electrical stack is one of the mechanical team’s top priorities. The stack is enclosed by an off-the-shelf Polycase capsule and a custom-machined aluminum plate with space for WetLink penetrators and SubConn connectors. The bottom plate is also anodized to ward off corrosion in saltwater environments.
This year, we added a new custom-made titanium top plate in response to a number of small leaks during last year’s competition. The four brass inserts molded into the Polycase capsule began to fail due to wear and tear over a year of use. The new titanium plate bypasses this weak point and applies even pressure across the entire capsule, improving performance and decreasing deterioration.
Component Mounts
The primary goals for all component mounts on Oogway are flexibility and rapid prototyping. Oogway’s aluminum rails allow us to move components around easily to optimize for factors such as buoyancy and placement of sensors. This year, this came in handy for the hydrophone mounts, which underwent several different designs and locations as the acoustics subteam developed their code.
We primarily use 3D-printed mounts to keep Oogway lightweight and allow for updated designs to be fabricated consistently and quickly. The battery mount, for example, broke frequently during last year’s competition. This year, we were able to quickly prototype and test new designs and print backups just in case. We also designed several new parts this year, such as a marker dropper, two new sonar mounts, three new camera mounts, and a new adjustable buoyancy system.
Actuators
We added actuators to Oogway for the first time this year. The marker dropper mechanism uses Blue Trail Engineering’s waterproof servo to hold up to two markers in place, and a rotation to either side allows these markers to be released. This gives us the flexibility to choose when the markers should be dropped and how many should be dropped at a time.
While not yet on Oogway, we are also prototyping a torpedo launcher using the same waterproof servo, which will be responsible for releasing the torpedoes. Like with the marker dropper, we aim to use one servo to control both triggers independently to give us the most flexibility during a run.
Full Model Assembly
As we add or update components on the robot, we also ensure that the full model assembly of Oogway remains up-to-date. The assembly allows us to visualize new components and identify conflicts before fabrication. This year, we also used the full model assembly to generate media materials for the website and paper to more effectively illustrate our prototyping process and final products.
In the future, we hope to integrate the assembly into our simulation workflow. For instance, this would enable our task planning team to roughly tune movement constants before putting the robot in the pool.