THESIS
2021
1 online resource (x, 67 pages) : illustrations (some color)
Abstract
Construction work is one of the least intelligent and automated industries in the world. With
the rapid development of robotics technology, a lot of companies and institutes explore how
robotics can be involved in construction work to improve efficiency, overcome labor
shortages and save cost. Since a large proportion of construction operations are incredibly
repetitive, construction robotics is expected to solve the disadvantage of manual labor and
manipulate more precisely. Automation is the key to meeting demand and autonomous mobile
robots are an integral part of construction automation which has a great number of application
scenarios. Different actuators can be embedded on the unmanned mobile chassis to fulfill
corresponding needs, such as laying, painting, leveling, inspection, e...[
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Construction work is one of the least intelligent and automated industries in the world. With
the rapid development of robotics technology, a lot of companies and institutes explore how
robotics can be involved in construction work to improve efficiency, overcome labor
shortages and save cost. Since a large proportion of construction operations are incredibly
repetitive, construction robotics is expected to solve the disadvantage of manual labor and
manipulate more precisely. Automation is the key to meeting demand and autonomous mobile
robots are an integral part of construction automation which has a great number of application
scenarios. Different actuators can be embedded on the unmanned mobile chassis to fulfill
corresponding needs, such as laying, painting, leveling, inspection, etc.
Localization plays a key role in the automation of mobile robots and it is an essential step for
further navigation and manipulation. This thesis addresses the problem of localizing a mobile
robot on the construction site for both indoor and outdoor environments. Lidar, RTK GPS,
inertial measurement units, and wheel encoders are combined to output accurate position
information with sensor fusion. Moreover, building information modeling(BIM) has been
increasingly adopted in the construction process and it contains geometric and semantic
information which can be exploited by construction robotics for a better understanding of the
environment. We also explore combining information from BIM for localization. Experiments
in both indoor and outdoor environments show a reasonable positioning result which can
enable further navigation.
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