Vision-based control of intelligent robot networks
It is observed that multi-robot systems are cheaper and more effective when compared to a single robot. However, the effectiveness of multi-robot systems in uncertain environments appears to lag natural formation control counterparts such as a swarm of ants and a flock of birds. This is because mobi...
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2022
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sg-ntu-dr.10356-1575572023-07-07T19:27:42Z Vision-based control of intelligent robot networks How, Jia Jin Hu Guoqiang School of Electrical and Electronic Engineering GQHu@ntu.edu.sg Engineering::Electrical and electronic engineering It is observed that multi-robot systems are cheaper and more effective when compared to a single robot. However, the effectiveness of multi-robot systems in uncertain environments appears to lag natural formation control counterparts such as a swarm of ants and a flock of birds. This is because mobile robots are usually programmed and tested in a controlled environment and rely heavily on global positioning and orientation data. Thus, in this project, formation control, obstacle avoidance and loss of vision correction algorithms are designed with the consideration of uncertain environment. The control algorithms mainly use vision-based data such as LIDAR sensor and cameras for control. MATLAB and Simulink software were used for the testing and simulation of the control algorithms designed. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-19T13:18:03Z 2022-05-19T13:18:03Z 2022 Final Year Project (FYP) How, J. J. (2022). Vision-based control of intelligent robot networks. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157557 https://hdl.handle.net/10356/157557 en application/pdf Nanyang Technological University |
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It is observed that multi-robot systems are cheaper and more effective when compared to a single robot. However, the effectiveness of multi-robot systems in uncertain environments appears to lag natural formation control counterparts such as a swarm of ants and a flock of birds. This is because mobile robots are usually programmed and tested in a controlled environment and rely heavily on global positioning and orientation data.
Thus, in this project, formation control, obstacle avoidance and loss of vision correction algorithms are designed with the consideration of uncertain environment. The control algorithms mainly use vision-based data such as LIDAR sensor and cameras for control. MATLAB and Simulink software were used for the testing and simulation of the control algorithms designed. |
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Hu Guoqiang |
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Hu Guoqiang How, Jia Jin |
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Final Year Project |
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How, Jia Jin |
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How, Jia Jin |
title |
Vision-based control of intelligent robot networks |
title_short |
Vision-based control of intelligent robot networks |
title_full |
Vision-based control of intelligent robot networks |
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Vision-based control of intelligent robot networks |
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Vision-based control of intelligent robot networks |
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vision-based control of intelligent robot networks |
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Nanyang Technological University |
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2022 |
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https://hdl.handle.net/10356/157557 |
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