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This paper provides a concise yet comprehensive review of spatial environment sensing and perception in automated systems, crucial for intelligent applications such as smart cities, smart homes, navigation, automated driving and industry 4.0. With a focus on achieving dependable performance even in harsh environments and enabling affordable mass deployment, the review explores sensor technologies, calibration, diagnostics, performance degradation analysis, and machine-learning-based perception algorithms. Our contributions aim to deepen understanding and drive progress in automated systems, addressing challenges across diverse application scenarios. Through a meticulous analysis of the pros and cons of state-of-the-art technologies, the paper sheds light on future trends in research and development. This work serves as a valuable resource for researchers, practitioners, and industry professionals seeking insights into the evolving landscape of spatial environment sensing and perception.
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Tai Fei
Jiangsu University
Subhas Chandra Mukhopadhyay
Macquarie University
João Paulo C. L. da Costa
Universidade de Brasília
IEEE Sensors Journal
Macquarie University
Xidian University
Indian Institute of Engineering Science and Technology, Shibpur
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Fei et al. (Mon,) studied this question.
synapsesocial.com/papers/6a20124e7110a651dc04f492 — DOI: https://doi.org/10.1109/jsen.2024.3379222