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61	Development of the Subwave ROV and Neural-Inertial Positioning System Farmer, Jason 09 August 2022 (has links) (PDF) This report documents the development of the Subwave, a remotely-operated underwater vehicle (ROV), and an artificial neural network based inertial positioning system. The Subwave uses the open-source ArduSub software framework, commercial-off-the-shelf hardware components, and several custom systems. It is designed as a platform for researching autonomous underwater vehicles (AUVs). The first step for an AUV is navigating waypoints, which requires the AUV to know its global position. Since global navigation satellite systems (GNSSs) are denied underwater, the available underwater positioning systems were surveyed and determined that all the available systems were too large and expensive for the Subwave. It was also discovered that the only consistent underwater positioning method was inertial positioning. So, experimentation began on a small, low-cost system that employs an artificial neural network to predict latitude and longitude using micro-electromechanical system (MEMS) inertial measurement unit (IMU) data as inputs, which would become the Neural-Inertial Positioning System. ROV AUV Underwater Robotics ArduSub GNSS-Denied Navigation Inertial Positioning Inertial Navigation Inertial Dead-Reckoning Neural-Inertial Positioning Signal Processing
62	Development of Sensors and Microcontrollers for Underwater Robots Jebelli, Ali January 2014 (has links) Nowadays, small autonomous underwater robots are strongly preferred for remote exploration of unknown and unstructured environments. Such robots allow the exploration and monitoring of underwater environments where a long term underwater presence is required to cover a large area. Furthermore, reducing the robot size, embedding electrical board inside and reducing cost are some of the challenges designers of autonomous underwater robots are facing. As a key device for reliable operation-decision process of autonomous underwater robots, a relatively fast and cost effective controller based on Fuzzy logic and proportional-integral-derivative method is proposed in this thesis. It efficiently models nonlinear system behaviors largely present in robot operation and for which mathematical models are difficult to obtain. To evaluate its response, the fault finding test approach was applied and the response of each task of the robot depicted under different operating conditions. The robot performance while combining all control programs and including sensors was also investigated while the number of program codes and inputs were increased. AUV Autonomous Underwater Vehicles ADC Analog to Digital Converter Cd Drag coefficient of the object DOF Degree of Freedom KT Thrust coefficient Fd Force of drag g Acceleration of gravity h Height of the fluid above the object KQ Torque coefficient mb Buoyant mass NN Neural network P Proportional controller PI Proportional-integral controller PID ρ Density of the fluid Q Torque of the propeller ROV Remotely Operated Vehicles RPM Speed of the motor or propeller SDO Serial data output SMC Sliding mode control Measured thrust T° Temperature v AV Advance speed of the propeller

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Development of the Subwave ROV and Neural-Inertial Positioning System

Development of Sensors and Microcontrollers for Underwater Robots