Quantitative trajectory evaluation criterion and long-term enhancement for multi-robot slam
Multi robot SLAM systems have several advantages e.g. robustness and quicker exploration, which determine they have better performance and importance than single robot SLAM especially in time critical Search and Rescure missions. However, the development of multi robot SLAM is much slower, because o...
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sg-ntu-dr.10356-785002023-07-04T16:14:35Z Quantitative trajectory evaluation criterion and long-term enhancement for multi-robot slam Liu, Xiangyu Wang Dan Wei School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Multi robot SLAM systems have several advantages e.g. robustness and quicker exploration, which determine they have better performance and importance than single robot SLAM especially in time critical Search and Rescure missions. However, the development of multi robot SLAM is much slower, because of the difficulties such as determination of relative poses of robots and communication, etc. CORB-SLAM as a multi robot SLAM system, of which the clients are based on ORB-SLAM2, inheriting its advantages like low-cost sensor configuration and low computation cost, has not been evaluated in a quantitative method to assess its performance. For multi robot SLAM, the adaptability in long-term scenarios is another important research topic, since multi robots may run in different dates and seasons. Because CORB-SLAM does not employ extra algorithms to suppress illumination changes, its long-term performance is limited. This work quantitatively evaluates CORB-SLAM, and experiments to combine it with illumination variance algorithm to improve its performance under different illumination and season. Master of Science (Computer Control and Automation) 2019-06-20T09:13:11Z 2019-06-20T09:13:11Z 2019 Thesis http://hdl.handle.net/10356/78500 en 65 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Liu, Xiangyu Quantitative trajectory evaluation criterion and long-term enhancement for multi-robot slam |
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Multi robot SLAM systems have several advantages e.g. robustness and quicker exploration, which determine they have better performance and importance than single robot SLAM especially in time critical Search and Rescure missions. However, the development of multi robot SLAM is much slower, because of the difficulties such as determination of relative poses of robots and communication, etc. CORB-SLAM as a multi robot SLAM system, of which the clients are based on ORB-SLAM2, inheriting its advantages like low-cost sensor configuration and low computation cost, has not been evaluated in a quantitative method to assess its performance. For multi robot SLAM, the adaptability in long-term scenarios is another important research topic, since multi robots may run in different dates and seasons. Because CORB-SLAM does not employ extra algorithms to suppress illumination changes, its long-term performance is limited. This work quantitatively evaluates CORB-SLAM, and experiments to combine it with illumination variance algorithm to improve its performance under different illumination and season. |
author2 |
Wang Dan Wei |
author_facet |
Wang Dan Wei Liu, Xiangyu |
format |
Theses and Dissertations |
author |
Liu, Xiangyu |
author_sort |
Liu, Xiangyu |
title |
Quantitative trajectory evaluation criterion and long-term enhancement for multi-robot slam |
title_short |
Quantitative trajectory evaluation criterion and long-term enhancement for multi-robot slam |
title_full |
Quantitative trajectory evaluation criterion and long-term enhancement for multi-robot slam |
title_fullStr |
Quantitative trajectory evaluation criterion and long-term enhancement for multi-robot slam |
title_full_unstemmed |
Quantitative trajectory evaluation criterion and long-term enhancement for multi-robot slam |
title_sort |
quantitative trajectory evaluation criterion and long-term enhancement for multi-robot slam |
publishDate |
2019 |
url |
http://hdl.handle.net/10356/78500 |
_version_ |
1772825430992093184 |