Obstacle avoidance path planning for the UR10 robotic manipulator: an improved RRT* algorithm
This dissertation focuses on the path planning of the UR10 robotic manipu- lator. Using the D-H method, the link coordinate frames for the UR10 are established, and both the forward and inverse kinematics are verified. Then this dissertation develops an improved RRT* algorithm. These improvements in...
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sg-ntu-dr.10356-1823182025-01-24T15:48:02Z Obstacle avoidance path planning for the UR10 robotic manipulator: an improved RRT* algorithm Gao, Luxuan Hu Guoqiang School of Electrical and Electronic Engineering GQHu@ntu.edu.sg Engineering This dissertation focuses on the path planning of the UR10 robotic manipu- lator. Using the D-H method, the link coordinate frames for the UR10 are established, and both the forward and inverse kinematics are verified. Then this dissertation develops an improved RRT* algorithm. These improvements include a goal-oriented strategy, a dynamic step strategy, K-d tree optimization, prun- ing, and path smoothing, aimed at increasing the efficiency and quality of path planning. Based on the foundation above, simulations are conducted in both 2D and 3D obstacle environments in MATLAB. The results demonstrate the superi- ority of the new algorithm compared to traditional RRT and RRT* algorithms. In addition, a UR10 robotic manipulator simulation system is also built in ROS environment, to verify the improved algorithm’s capability in practical applica- tions. Master's degree 2025-01-21T08:50:55Z 2025-01-21T08:50:55Z 2025 Thesis-Master by Coursework Gao, L. (2025). Obstacle avoidance path planning for the UR10 robotic manipulator: an improved RRT* algorithm. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/182318 https://hdl.handle.net/10356/182318 en application/pdf Nanyang Technological University |
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This dissertation focuses on the path planning of the UR10 robotic manipu- lator. Using the D-H method, the link coordinate frames for the UR10 are established, and both the forward and inverse kinematics are verified. Then this dissertation develops an improved RRT* algorithm. These improvements include a goal-oriented strategy, a dynamic step strategy, K-d tree optimization, prun- ing, and path smoothing, aimed at increasing the efficiency and quality of path planning. Based on the foundation above, simulations are conducted in both 2D and 3D obstacle environments in MATLAB. The results demonstrate the superi- ority of the new algorithm compared to traditional RRT and RRT* algorithms. In addition, a UR10 robotic manipulator simulation system is also built in ROS environment, to verify the improved algorithm’s capability in practical applica- tions. |
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Hu Guoqiang |
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Hu Guoqiang Gao, Luxuan |
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Thesis-Master by Coursework |
author |
Gao, Luxuan |
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Gao, Luxuan |
title |
Obstacle avoidance path planning for the UR10 robotic manipulator: an improved RRT* algorithm |
title_short |
Obstacle avoidance path planning for the UR10 robotic manipulator: an improved RRT* algorithm |
title_full |
Obstacle avoidance path planning for the UR10 robotic manipulator: an improved RRT* algorithm |
title_fullStr |
Obstacle avoidance path planning for the UR10 robotic manipulator: an improved RRT* algorithm |
title_full_unstemmed |
Obstacle avoidance path planning for the UR10 robotic manipulator: an improved RRT* algorithm |
title_sort |
obstacle avoidance path planning for the ur10 robotic manipulator: an improved rrt* algorithm |
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Nanyang Technological University |
publishDate |
2025 |
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https://hdl.handle.net/10356/182318 |
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1823108698209255424 |