⏩ Volume 22, Issue No.4, 2024 (ISR)
Robotic Systems for Autonomous Navigation in Urban Environments: Challenges and Future Directions

This paper examines the challenges and future directions for developing robotic systems capable of autonomous navigation in complex urban environments. It highlights the importance of advanced algorithms, real-time data processing, and decision-making capabilities to enable robots to navigate safely and efficiently in unpredictable settings.

Michael Christopher Taylor, Jessica Maria Roberts, David Thomas Williams, Olivia Grace Mitchell, Ethan James Harris

Paper ID: 52422401
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Advancements in AI-Powered Robot Vision for Industrial Automation: A Comprehensive Review

This review paper covers the latest advancements in AI-powered robotic vision systems, which are revolutionizing industrial automation. It explores applications such as quality control, object detection, and process optimization, all of which contribute to increased productivity and reduced human intervention in manufacturing environments.

Samuel John Anderson, Sophie Claire Mitchell, William George Hall, Charlotte Marie Davis, Benjamin Thomas Wright

Paper ID: 52422402
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Swarm Robotics: A New Paradigm for Collaborative Multi-Robot Systems in Autonomous Environments

Swarm robotics explores the ability of multiple robots to work collaboratively towards achieving a common goal. This paper explores the potential of swarm robotics in autonomous systems, particularly in applications such as search and rescue operations, environmental monitoring, and distributed manufacturing systems.

David Michael Davis, Clara Jane Miller, Thomas Andrew Smith, Emma Lily Clark, Noah Benjamin Robinson

Paper ID: 52422403
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AI-Driven Robotic Systems for Hazardous Waste Cleanup: Current Trends and Future Prospects

This research paper discusses the use of AI-driven robotic systems in hazardous waste cleanup operations. The paper outlines the challenges faced by robotic systems in extreme environments and how AI and machine learning can be applied to improve the accuracy, efficiency, and safety of the cleanup process.

James Christopher Williams, Elizabeth Victoria Green, Nicholas Patrick Martin, Olivia Helen Carter, Thomas George Walker

Paper ID: 52422404
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Optimizing Robot Path Planning in Dynamic Environments Using Deep Reinforcement Learning

This paper explores the use of deep reinforcement learning algorithms for robot path planning in dynamic environments. It emphasizes the importance of continuous learning, real-time feedback, and adaptability to enhance a robot's ability to navigate through changing and unpredictable scenarios in real-world applications.

William Charles Thomas, Elizabeth Sarah Robinson, John David Peterson, Lucy Anne Brooks, Joseph Andrew Harris

Paper ID: 52422405
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Applications of Robotic Systems in Disaster Relief and Humanitarian Efforts

This study examines the role of robotic systems in disaster relief operations and humanitarian aid efforts. It discusses how robots can assist in delivering supplies, rescuing victims, and assessing damage in areas that are hazardous or inaccessible to human responders, making them valuable tools in crisis situations.

David Robert Morgan, Patricia Marie Thompson, William Stephen Young, Nicholas Charles Evans, Elizabeth Margaret Brown

Paper ID: 52422406
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