BIM based robot assisted object detection
In the 21st Century, attributing to the rapid advancements in technology, automation is a rather prevalent area of focus. The key idea behind automation is to make a situation where simple and mundane jobs can be carried out without humans and hence, allowing this limited workforce to focus on hi...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/167894 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Summary: | In the 21st Century, attributing to the rapid advancements in technology, automation
is a rather prevalent area of focus. The key idea behind automation is to make a
situation where simple and mundane jobs can be carried out without humans and
hence, allowing this limited workforce to focus on higher skilled activities that can
only be done by humans. Currently, in the context of building and construction, various
types of robots are being used to achieve the push towards automation. Not only do
these robots free up certain portions of the workforce to focus on higher skilled
activities, they also help to boost efficiency of the process as well as ensure safety for
the workers. For example, humans would no longer be required to go into certain
hazardous or hard to reach areas to carry out these manual inspections. Similarly, the
scope of this project would be to implement a BIM-based Navigation algorithm and a
YOLOv3 Object Detection algorithm onto an Autonomous Mobile Robot (AMR) and
test it for its reliability and effectiveness. In particular, it would tackle an ever prevalent
issue of a dynamic working environment (ie. initially supplied goal pose is blocked by
an obstacle) and implement a reactive action to this issue. In addition, it would also
propose a solution which would enable multiple robots to be controlled on a single
platform, as there is an increasing need for interoperability between various different
types of robots in a shared workspace. The proposed algorithms have all been tested
for their effectiveness in the EEE Robotics Lab. |
---|