This study investigates the use of deep reinforcement learning (DRL) and computer vision for enhancing autonomous robot navigation in unknown environments. The combination of these techniques enables robots to make decisions in real-time, improving their performance in tasks such as mapping, obstacle avoidance, and exploration.

John Michael Anderson, Sarah Katherine Lee, Ethan Joseph Clark, Emma Olivia Davis

This paper explores the design and implementation of a smart robotic arm for precise industrial assembly. It integrates advanced sensors, AI-based control systems, and real-time data processing to handle delicate materials and automate assembly tasks, significantly reducing human intervention and improving productivity in manufacturing.

David William Harris, Ava Grace Scott, Mason Joseph Thompson, Sophia Emma Walker

This paper presents a machine learning-based autonomous drone system for precision agriculture. The system uses computer vision and AI to monitor crop health, detect pests, and assess environmental conditions. The drones are designed to perform targeted interventions, optimizing pesticide use and enhancing overall crop yield.

Lucas Benjamin Ford, Isabella Amelia Green, Charles Evan Murphy, Olivia Sophia Bennett

This research focuses on AI-driven robotic surgery systems designed for minimally invasive operations. The systems provide enhanced precision and adaptability in surgeries, using AI algorithms to assist in real-time decision-making, improving patient outcomes, and reducing recovery times while ensuring greater safety during complex procedures.

Victoria Olivia Martin, Nicholas Alexander Taylor, Abigail Rose Harris, Gabriel Thomas Williams

This paper discusses the design of autonomous mobile robots specifically developed for hazardous material handling in nuclear power plants. The robots are equipped with AI-driven systems for safe operation in high-radiation areas, reducing human exposure and improving efficiency in handling dangerous materials.

William Henry Clark, Eleanor Margaret Turner, Marcus Robert White, Naomi Grace Peterson

This study investigates human-robot interaction (HRI) in collaborative workspaces. The paper examines how robots and humans can efficiently and safely work together in manufacturing environments, focusing on task allocation, communication protocols, and safety measures to ensure optimal collaboration without compromising productivity or safety.

Daniel James Parker, Olivia Sophia Adams, Grace Lily Robinson, Samuel Noah Thompson

This research focuses on AI-based navigation systems for autonomous vehicles operating in complex urban environments. By integrating advanced machine learning algorithms with real-time sensor data, the system enhances vehicle autonomy, enabling precise decision-making and efficient navigation through dense city traffic and unpredictable road conditions.

Lucas Benjamin Ford, Olivia Grace Mitchell, Ethan Joseph Martin, Amelia Lily Clark