This research presents an autonomous robotic system designed for detecting hazardous materials in industrial environments. The system integrates advanced sensors, machine learning algorithms, and real-time data processing to identify, locate, and safely handle hazardous substances, ensuring worker safety and compliance with environmental regulations.

Oliver John Mitchell, Amelia Caroline Williams, Benjamin Daniel Hall, Isabella Anne Parker, Thomas Alexander Scott

This study focuses on AI-driven precision farming robots that utilize machine learning and computer vision technologies to optimize crop management. By analyzing soil conditions, weather data, and plant health, these robots automate irrigation, fertilization, and pest control, promoting sustainable and efficient agricultural practices.

Charlotte Grace Miller, William Thomas Brown, Olivia Sophia Harris, Jack Andrew Taylor, Robert James Wilson

This paper investigates robust path planning algorithms for autonomous mobile robots navigating dynamic urban environments. By using real-time sensor data and dynamic re-routing algorithms, the proposed system can efficiently avoid obstacles, handle traffic congestion, and adapt to rapidly changing conditions in urban spaces.

Eva Marie Johnson, Simon Louis Clark, Thomas William Green, Marie Catherine Adams, James Charles Walker

This paper explores the use of deep convolutional neural networks (CNNs) to enhance object detection in autonomous vehicles. By training the CNN on large-scale traffic datasets, the system improves vehicle safety by accurately identifying pedestrians, other vehicles, and obstacles in real-time under various driving conditions.

George Henry Thomas, Mary Elizabeth Hall, James Edward Lee, Natalie Ruth Harris, David Alan Young

This study focuses on the application of machine learning algorithms for predictive maintenance in industrial robotics. By analyzing historical sensor data and operational metrics, the proposed model predicts potential system failures, helping to reduce downtime and maintenance costs in manufacturing environments.

Daniel Henry Carter, Patricia Michelle Johnson, Brian Andrew Martin, Thomas Jason Moore, Sarah Natalie Evans

This research focuses on multi-robot systems for search and rescue operations in hazardous environments. The system uses a combination of autonomous robots to locate and assist victims in situations like natural disasters, hazardous material spills, and collapsed buildings, ensuring faster response and increased safety.

Charlotte Grace Lee, Matthew William Clark, Anna Marie Taylor, Daniel Joseph White, Henry Jacob King

This paper explores deep learning techniques for real-time object tracking in autonomous surveillance systems. By utilizing convolutional neural networks and recurrent neural networks, the system can efficiently track moving objects in dynamic environments, improving the performance and reliability of surveillance robots in security applications.

Alexander James Thompson, Sophia Alice White, Lucas Henry Davis, Emily Grace Moore, Samuel William Wilson