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Axis-coupled trajectory generation for chains of integrators through smoothing splines

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Abstract

Integrator based model is used to describe a wide range of systems in robotics. In this paper, we present an axis-coupled trajectory generation algorithm for chains of integrators with an arbitrary order. Special notice has been given to problems with pre-existing nominal plans, which are common in robotic applications. It also handles various type of constraints that can be satisfied on an entire time interval, including non-convex ones which can be transformed into a series of convex constraints through time segmentation. The proposed approach results in a linearly constrained quadratic programming problem, which can be solved effectively with off-the-shelf solvers. A closed-form solution is achievable with only the boundary constraints considered. Finally, the proposed method is tested in real experiments using quadrotors which represent high-order integrator systems.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117583, Singapore

    Shupeng Lai, Kehong Gong & Ben M. Chen

  2. Graduate School for Integrative Science & Engineering, National University of Singapore, Singapore, 119077, Singapore

    Menglu Lan

  3. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China

    Ben M. Chen

Authors
  1. Shupeng Lai
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  2. Menglu Lan
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  3. Kehong Gong
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  4. Ben M. Chen
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Corresponding author

Correspondence to Shupeng Lai.

Additional information

Shupeng LAI received his B.Eng (1st) degree in Electrical and Electronics Engineering from Nanyang Technological University and his Ph.D. degree from the National University of Singapore. He is currently working as a research fellow in the National University of Singapore. His research interest is in mobile robots motion planning and control.

Menglu LAN received her B.Eng (1st) degree in Electrical and Computer Engineering from National University of Singapore (NUS) in 2015. She is currently pursuing her Ph.D. degree in NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, with research interest in task and motion planning for micro sized aerial vehicles (MAVs).

Kehong GONG studied in Nation University of Singapore since 2012, and received the B.Eng. degree in Engineering Science Program in 2017. He started working with UAV in year 3 summer vocation, and continued working on it in his final year program. After graduation, he worked as a research engineer in the Unmanned Systems Research Group at the National University of Singapore. His research interests are in robotics and artificial intelligence.

Ben M. CHEN is currently a Professor in the Department of Mechanical and Automation Engineering, the Chinese University of Hong Kong. He was a Provost Chair Professor in the Department of Electrical and Computer Engineering, the National University of Singapore (NUS), where he was also serving as the Director of Control, Intelligent Systems and Robotics Area, and Head of Control Science Group, NUS Temasek Laboratories. His current research interests are in unmanned systems, robust control, control applications, and financial market modeling. Dr. Chen has published more than 400 journal and conference articles, and a dozen research monographs in control theory and applications, unmanned systems as well as financial market modeling. He had served on the editorial boards of several international journals including IEEE Transactions on Automatic Control and Automatica. He currently serves as an Editorin-Chief of Unmanned Systems. Dr. Chen has received a number of research awards nationally and internationally. His research team has actively participated in international UAV competitions, and won many championships in the contests. He is an IEEE Fellow.

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Lai, S., Lan, M., Gong, K. et al. Axis-coupled trajectory generation for chains of integrators through smoothing splines. Control Theory Technol. 17, 48–61 (2019). https://doi.org/10.1007/s11768-019-8201-y

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  • DOI: https://doi.org/10.1007/s11768-019-8201-y

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