TY - GEN
T1 - Autonomous Delivery Vehicle System Based on Multi-Sensor Data Fusion
AU - Lei, Runyu
AU - Tang, Longbin
AU - Guo, Jiaxin
AU - Sun, Jie
AU - Bu, Qinglei
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - With the rapid advancement of science and technology, people's yearning for a more convenient life has gradually become concrete, which has given rise to a huge logistics industry chain. At the same time, the ever-increasing labor costs have caused an urgent need for autonomous delivery vehicles. This paper presents the design and integration of an autonomous vehicle system for efficient indoor parcel delivery, addressing the challenges of navigating dynamic indoor environments. This vehicle system leverages a multi-sensor approach, integrating LiDAR, radar, Inertial Measurement Unit (IMU), GPS, and odometer data to provide comprehensive environmental perception and precise localization, which will contribute to the field by providing a practical application of autonomous vehicle technology in a constrained environment, offering a solution for the logistics industry's indoor delivery challenges.
AB - With the rapid advancement of science and technology, people's yearning for a more convenient life has gradually become concrete, which has given rise to a huge logistics industry chain. At the same time, the ever-increasing labor costs have caused an urgent need for autonomous delivery vehicles. This paper presents the design and integration of an autonomous vehicle system for efficient indoor parcel delivery, addressing the challenges of navigating dynamic indoor environments. This vehicle system leverages a multi-sensor approach, integrating LiDAR, radar, Inertial Measurement Unit (IMU), GPS, and odometer data to provide comprehensive environmental perception and precise localization, which will contribute to the field by providing a practical application of autonomous vehicle technology in a constrained environment, offering a solution for the logistics industry's indoor delivery challenges.
KW - Autoware.Universe
KW - LiDAR SLAM
KW - Multi-Sensor Data Fusion
KW - Path Planning
UR - http://www.scopus.com/inward/record.url?scp=85219525603&partnerID=8YFLogxK
U2 - 10.1109/IRAC63143.2024.10871795
DO - 10.1109/IRAC63143.2024.10871795
M3 - Conference Proceeding
AN - SCOPUS:85219525603
T3 - 2024 International Conference on Intelligent Robotics and Automatic Control, IRAC 2024
SP - 24
EP - 30
BT - 2024 International Conference on Intelligent Robotics and Automatic Control, IRAC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 International Conference on Intelligent Robotics and Automatic Control, IRAC 2024
Y2 - 29 November 2024 through 1 December 2024
ER -