Autonomous Embodied AI by Xin Wang (.ePUB)+
File Size: 29.6 MB
Autonomous Embodied AI: Towards Self-evolving Intelligence by Xin Wang, Tongtong Feng, Huaping Liu, Wenwu Zhu
Requirements: .ePUB, .PDF reader, 29.6 MB | True PDF, True EPUB
Overview: This book offers a concise yet comprehensive exploration of embodied Artificial Intelligence (AI) and its integration with swarm manipulation, navigation, and tracking tasks. It uniquely bridges the gap in the existing literature by providing a thorough review of swarm-embodied AI, focusing on collaborative perception and decision-making methods. Its standout features include a systematic approach, detailed discussions on advanced directions, and a practical case study on multi-robot multi-target tracking. Embodied Artificial Intelligence (AI) has emerged as a cornerstone in advancing intelligent systems, highlighting that cognition and reasoning cannot be decoupled from perception and interaction with the physical world. Unlike purely digital intelligence, embodied AI enables agents to ground abstract reasoning in real-world contexts, thereby bridging the gap between virtual and physical worlds. As large-scale AI models have demonstrated unprecedented reasoning ability, this embodied paradigm provides a natural pathway for extending intelligence to dynamic, uncertain, and open environments, which is critical for realizing Artificial General Intelligence (AGI). It commences by examining the three key elements of embodied AI: multi-sensor fusion, embodied perception, and embodied decision-making. It reviews existing works that independently optimize each of these elements. Subsequently, the book delves into swarm-embodied AI, encompassing swarm-embodied collaborative perception, collaborative decision-making, and future research directions. Specifically, it explores how swarm intelligence enhances the scalability and generalizability of embodied AI, and conversely, how embodied AI augments Swarm Intelligence by adapting learning models to diverse tasks and environments. Finally, the book presents a case study of multi-robot multi-target tracking, providing a practical demonstration of all algorithms discussed within. Readers can follow this case study step by step to gain a deeper understanding of the advancements and potential challenges of swarm-embodied AI.
Genre: Non-Fiction > Tech & Devices
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