Fog-based Edge AI for Robotics: Cutting-edge Research and Future Directions

Abstract

The fusion of Fog-based Edge Artificial Intelligence (AI) is an emerging and transformative research area within robotics. This research examines the significant potential of augmenting robotic systems by integrating Edge AI and Fog Computing, aiming to enhance their cognitive abilities, independence, and operational effectiveness. The feasibility of real-time data analysis and decision-making is enhanced by deploying AI algorithms at the network edge, near the robots, and by leveraging fog computing capabilities. This study investigates the diverse implementations of Fog-based artificial intelligence (AI) in robotics. These applications encompass autonomous navigation, object detection, and human-robot interaction. By showcasing these examples, the research demonstrates the potential for a transformative impact on the capabilities of robotic systems through the integration of Fog-based AI. Additionally, this study explores the obstacles and potential advantages within this interdisciplinary field, providing valuable perspectives on the promising avenues that can facilitate advancements in robotics by leveraging the combined power of Fog-based Edge Artificial Intelligence. This study elucidates how the amalgamation of Fog Computing and Edge AI confers enhanced capabilities upon intelligent robotic systems, enabling them to operate autonomously in real time. This integration effectively addresses the obstacles commonly encountered in conventional cloud-based AI systems, such as latency, internet connectivity, and data security concerns. The study highlights the importance of architecture, security, and ethical factors in utilizing robotic intelligence. It emphasizes the need for data protection standards and transparency to ensure responsible and reliable utilization of this technology in a rapidly changing environment.