Time-optimal motion planning and control
The recent years have seen rapid growth in the adoption of robotics technologies. This welcoming development has led to increasingly complex applications with stringent requirements, motivating research on time-optimal motion planning and control for robots. This thesis presents developments tha...
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sg-ntu-dr.10356-835462023-03-11T17:36:24Z Time-optimal motion planning and control Pham, Tien Hung Pham Quang Cuong School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering::Robots The recent years have seen rapid growth in the adoption of robotics technologies. This welcoming development has led to increasingly complex applications with stringent requirements, motivating research on time-optimal motion planning and control for robots. This thesis presents developments that extend the state-of-the-art in time-optimal motion planning and control for robots. I first revisit a classical problem in the robotic literature--computing the Time-Optimal Path Parameterization along a specified path--which was posed more than 30 years ago by (Bobrow, 1985). The presented new approach to the problem, as suggested by experimental evaluations, outperforms existing solutions in both computational complexity and robustness. Next, I discuss an experimental case study of an industrial task: planning critically fast motions for robots transporting objects with suction cups. Experimental results suggest that by appropriately modelling of ``suction cup constraints'', one can control an industrial robot at high speed (near the robot hardware speed limit) and still achieve 100\% transport success rate. Finally, I discuss and present solutions to two issues that are commonly associated with the use of Time-Optimal Path Parameterizations: (i) the existence of switching points with infinite joint jerk and (ii) the poor regulation of tracking error. Doctor of Philosophy 2019-08-26T00:51:00Z 2019-12-06T15:25:19Z 2019-08-26T00:51:00Z 2019-12-06T15:25:19Z 2019 Thesis Pham, T. H. (2019). Time-optimal motion planning and control. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/83546 http://hdl.handle.net/10220/49772 10.32657/10220/49772 en 168 p. application/pdf |
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Engineering::Mechanical engineering::Robots Pham, Tien Hung Time-optimal motion planning and control |
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The recent years have seen rapid growth in the adoption of robotics technologies. This welcoming development has led to increasingly complex applications with stringent requirements, motivating research on time-optimal motion planning and control for robots.
This thesis presents developments that extend the state-of-the-art in time-optimal motion planning and control for robots. I first revisit a classical problem in the robotic literature--computing the Time-Optimal Path Parameterization along a specified path--which was posed more than 30 years ago by (Bobrow, 1985). The presented new approach to the problem, as suggested by experimental evaluations, outperforms existing solutions in both computational complexity and robustness. Next, I discuss an experimental case study of an industrial task: planning critically fast motions for robots transporting objects with suction cups. Experimental results suggest that by appropriately modelling of ``suction cup constraints'', one can control an industrial robot at high speed (near the robot hardware speed limit) and still achieve 100\% transport success rate. Finally, I discuss and present solutions to two issues that are commonly associated with the use of Time-Optimal Path Parameterizations: (i) the existence of switching points with infinite joint jerk and (ii) the poor regulation of tracking error. |
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Pham Quang Cuong |
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Pham Quang Cuong Pham, Tien Hung |
format |
Theses and Dissertations |
author |
Pham, Tien Hung |
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Pham, Tien Hung |
title |
Time-optimal motion planning and control |
title_short |
Time-optimal motion planning and control |
title_full |
Time-optimal motion planning and control |
title_fullStr |
Time-optimal motion planning and control |
title_full_unstemmed |
Time-optimal motion planning and control |
title_sort |
time-optimal motion planning and control |
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2019 |
url |
https://hdl.handle.net/10356/83546 http://hdl.handle.net/10220/49772 |
_version_ |
1761781393786929152 |