Titlebook: Autonomous Driving Perception; Fundamentals and App Rui Fan,Sicen Guo,Mohammud Junaid Bocus Book 2023 The Editor(s) (if applicable) and The

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Collaborative 3D Object Detection,individual vehicles results in the bottleneck of improvement of the 3D detection performance. To break through the limits of individual detection, collaborative 3D object detection has been proposed which enables agents to share information to perceive the environments beyond line-of-sight and field

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,Enabling Robust SLAM for?Mobile Robots with?Sensor Fusion,ress in solving the probabilistic SLAM problem by presenting various theoretical frameworks, efficient solvers, and complete systems. As the development of autonomous robots (i.e., self-driving cars, legged robots) continues, SLAM systems have become increasingly popular for large-scale real-world a

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Multi-task Perception for Autonomous Driving,, many self-supervised pre-training methods have been proposed and they have achieved impressive performance on a range of computer vision tasks. However, their generalization ability to multi-task scenarios is yet to be explored. Besides, most multi-task algorithms are designed for specific tasks u

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,Bird’s Eye View Perception for?Autonomous Driving,, map segmentation, and motion prediction. Due to its inherent advantages in representing 3D space, fusing multi-modal data, facilitating decision making, and aiding in path planning, BEV perception has garnered significant attention from both academia and industry. In this chapter, we present an ov

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Background and Traditional Approaches,e summary of evaluation metrics used to assess semantic segmentation results, along with corresponding benchmarks for a number of classic datasets, is also presented. Finally, practical applications of semantic segmentation in autonomous driving are explored, and conclusions are drawn on the current

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Traditional Graph Generation Approaches jointly use object features and point features to estimate camera 6-Degrees Of Freedom (6-DOF) poses and do richer map construction. Experiments are conducted using the proposed datasets and criteria with several state-of-the-art VSLAM methods to demonstrate the functionality of our datasets. Owing

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