⏩ Volume 21, Issue No.5, 2023 (ISR)
Advancements in Autonomous Robotics for Complex Terrain Navigation Using AI and Deep Learning Techniques in Disaster Management

This paper explores autonomous robots for navigating complex terrains in disaster management. By utilizing AI and deep learning algorithms, the robots can autonomously adapt to changing environments, offering efficient and safe solutions for search-and-rescue operations in disaster-stricken areas.

David Edward Miller, Lucas Alexander Johnson, Anna Michelle Harris, Christopher John Thompson, Isabelle Grace Morgan

Paper ID: 52321501
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Implementing Deep Reinforcement Learning in Autonomous Robots for Real-Time Path Planning in Dynamic Environments for Emergency Response Operations

This research investigates the use of deep reinforcement learning (DRL) in autonomous robots for real-time path planning in dynamic environments. The application of DRL ensures optimal route selection, enabling robots to navigate obstacles and complete emergency response operations efficiently and safely.

Emily Sophia Jackson, Sarah Olivia Wilson, Daniel Thomas Clark, Michael Charles Roberts, Julia Isabelle Walker

Paper ID: 52321502
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Collaborative Multi-Robot Systems for Large-Scale Environmental Monitoring in Agricultural and Industrial Settings Using Cloud Computing and AI Integration

This paper explores multi-robot systems in large-scale environmental monitoring across agricultural and industrial sectors. By integrating cloud computing and AI, these systems can efficiently collect, analyze, and transmit data, supporting sustainable practices and enabling real-time decision-making for improved productivity and environmental preservation.

John Michael Anderson, Olivia Claire Robinson, Ethan Samuel Clark, Grace Olivia Thompson, Lucas John Walker

Paper ID: 52321503
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Optimizing Robotic Manufacturing Systems for Precision Engineering and High-Volume Production Using Machine Learning Algorithms and Robotics

This research focuses on optimizing robotic manufacturing systems for precision engineering and high-volume production. By integrating machine learning algorithms, robotic systems can adapt to variations in production processes, ensuring higher quality, faster throughput, and reduced error rates in precision-based manufacturing tasks.

James Alexander Taylor, Lily Grace Brown, William Samuel Harris, Benjamin Thomas Scott, Emily Victoria Moore

Paper ID: 52321504
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Designing Autonomous Swarm Robotics for Hazardous Material Handling and Storage in Industrial Facilities Using AI and Advanced Control Systems

This paper explores autonomous swarm robotics for handling hazardous materials in industrial facilities. By incorporating AI and advanced control systems, these robots can safely perform dangerous tasks such as handling, transport, and storage, ensuring better safety and compliance with industrial safety standards.

Lucas Benjamin Davis, Hannah Maria Parker, Nathan Samuel Robinson, Clara Louise Walker, Jack Daniel Lee

Paper ID: 52321505
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