Effective Motion Sensors and Deep Learning Techniques for Unmanned Ground Vehicle (UGV)-Based Automated Pavement Layer Change Detection in Road Construction
As-built progress of the constructed pavement should be monitored effectively to provide prompt project control. However, current pavement construction progress monitoring practices (e.g., data collection, processing, and analysis) are typically manual, time-consuming, tedious, and error-prone. To a...
Main Authors: | Tirth Patel, Brian H. W. Guo, Jacobus Daniel van der Walt, Yang Zou |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-12-01
|
Series: | Buildings |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-5309/13/1/5 |
Similar Items
-
ROADS—Rover for Bituminous Pavement Distress Survey: An Unmanned Ground Vehicle (UGV) Prototype for Pavement Distress Evaluation
by: Alessandro Mei, et al.
Published: (2022-04-01) -
Fabrics and meshes in roads and other pavements : a state of the art review/
by: 457422 Ruddock, E. C.
Published: (1977) -
A Systematic Review of Automated Construction Inspection and Progress Monitoring (ACIPM): Applications, Challenges, and Future Directions
by: Reihaneh Samsami
Published: (2024-03-01) -
Platform-independent visual installation progress monitoring for construction automation
by: Zhao, Xinge, et al.
Published: (2023) -
Steel gratings as an innovative temporary roads pavement
by: Artur Juszczyk, et al.
Published: (2016-04-01)