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Part of book or chapter of book . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Part of book or chapter of book . 2025
License: CC BY
Data sources: Datacite
ZENODO
Part of book or chapter of book . 2025
License: CC BY
Data sources: Datacite
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Advancing Edge AI Perception Platforms and Sensor Fusion for Last-Mile Delivery Autonomous Vehicles

Authors: Vermesan, Ovidiu;

Advancing Edge AI Perception Platforms and Sensor Fusion for Last-Mile Delivery Autonomous Vehicles

Abstract

The intersection of edge artificial intelligence (AI), autonomous systems, robotics, and sensor fusion in perception and navigation advances the development of last-mile delivery autonomous vehicle (AV) platforms that evolve towards software-defined and AI-defined vehicles (SDVs and ADVs). The advancements include multiple sensor systems for perception and communication (e.g., ultrasound, inertial, LiDAR, radar, camera, V2X, etc.), real-time data processing for localisation, and robust algorithms for navigation and interaction with diverse traffic environments. This chapter presents the concept and the implementation of an AI-based perception and sensor fusion platform technical solution for autonomous last-mile delivery in controlled traffic environments.

Keywords

Artificial Intelligence, Autonomous robots, Autonomous vehicles

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green