Spatial Environment Perception and Sensing in Automated Systems: A Review
Tai Fei, Subhas Chandra Mukhopadhyay, João Paulo C. L. da Costa, C. RoyChaudhuri, Lan Lan, Nevine Demitri
Abstract
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.