Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/140352
Title: On-board 3-D SLAM for AGV localization
Authors: Chen, Yongyao
Keywords: Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
Issue Date: 2020
Publisher: Nanyang Technological University
Project: A1241-191
Abstract: Human detection is an essential task for a SLAM system in dynamic environment, such as warehouses, where the robot shares its workspace and interacts closely with operating personnel. Being aware of the real-time locations of humans in the scene is the basis for safe operation of the system. This final year project presents a 3D LiDAR SLAM system with an efficient human classification function that utilizes human geometry and state-of-the-art machine learning techniques to accurately identify human clusters in complex 3D point clouds. The performance of the system is evaluated with firsthand data from the Delta-NTU Corporate Laboratory for Cyber-Physical Systems. Experiments show the combination of the anthropometric and SVM classifiers produces decent human classification results in warehouse environment with medium to high complexity.
URI: https://hdl.handle.net/10356/140352
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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