Autonomous Fishing Using UAVs
The Autonomous Fishing Using UAVs project is a remarkable fusion of technology and tradition. Our students have engineered a UAV system that carries a sonar sensor to locate fish, subsequently deploying a fishing hook to precise locations. This ingenious approach integrates man’s age-old fishing techniques with modern technology, creating an efficient and automated method of fishing.
Beyond the confines of the lab, the team ventured into real-world testing by conducting multiple trials of their fully functional prototype at local lakes. Their holistic approach to the project encompassed a range of tasks, including sizing and selecting system elements, creating CAD designs, 3D printing components, coding the UAV’s motor system, and programming the microcontroller to ensure seamless operation. These real-world tests provided critical validation, offering invaluable insights into the system’s capabilities and solidifying the project’s feasibility for real-world applications.
Steering Wheel Data Connection and Simulations
The Steering Wheel Data Connection and Simulations project showcases the synergy between virtual reality and hardware control. Utilizing the Logitech G29 DrivingForce Racing Wheel, a student has created a connection with the Webots simulator, allowing for realistic control of a virtual car equipped with LiDAR. This simulation not only reduces costs but also opens avenues for future autonomous driving research, with an emphasis on geometry over textures and colors.
Air Pollution Detection Using LiDAR
The air pollution detection using LiDAR project highlights our students’ commitment to environmental responsibility and technological innovation. Utilizing LiDAR to scan gases, the project yields data that can be used to determine gas quality, identify specific gases, and calculate pollutant concentrations. This remarkable initiative holds the promise of more accurate and immediate air quality assessments, contributing to healthier living environments.
The students involved in the Air Pollution Detection Using LiDAR project not only demonstrated exceptional technical skills but also achieved significant academic and competitive accolades. Their innovative work was recognized at a prestigious conference, where they published their research findings. Moreover, their exceptional ability to convey complex technical information in an accessible manner led them to win the Missouri S&T ECE Senior Design Poster Competition. These achievements serve as a testament to their dedication, competence, and potential in contributing to groundbreaking research.
Publication
- Z. Osterwisch, A. Mauntel, N. Nisbett, D. Barua and A. Alsharoa, “Particulate Matter Detection in Mines Using 3D Light Detection and Ranging Technology,” in proc. of the IEEE Wireless Communication and Networking Conference (WCNC), Glasgow, UK, Mar. 2023.
Awards
- First Place Award: Spring 2022 Senior Design 2 Poster Competition.
- First Place Award: Fall 2021 Senior Design 1 Poster Competition.
Human Activity Recognition Using Webots
In the human activity recognition using Webots simulator, the students aim to collect LiDAR data for understanding human activities within a virtual environment. By using Webots to create simulations, they’ve laid the groundwork for deeper exploration into human behavior. This method of data collection is both cost-effective and innovative, potentially transforming the way we study and recognize human activity.
The success of the Human Activity Recognition Using Webots project extends beyond the lab, as our students have had the distinction of publishing their research findings. This accomplishment marks a significant milestone, showcasing the project’s impact and the students’ contributions to the field. For a deeper dive into the intricacies and innovative solutions developed during this project, we warmly invite you to explore the published work.
Publication
- O. Rinchi, N. Nisbett and A. Alsharoa, “Patients Arms Segmentation and Gesture Identification Using Standalone 3-D LiDAR Sensors,” in EEE Sensors Letters, July 2023.
JetBot LiDAR Control
The JetBot LiDAR Control project is an exceptional demonstration of how autonomous driving can be simulated and optimized. Students have employed JetBot and Jetson Nano to create real-time driving recommendations based on LiDAR scans of the environment. This project not only enhances our understanding of autonomous driving but also illustrates the potential for LiDAR to enhance safety and efficiency on the road.
