Maximizing ollie height by optimizing control strategy and skateboard geometry using direct collocation

Journal Article (2024)
Authors

Jan T. Heinen (Student TU Delft)

S.G. Brockie (TU Delft - Biomechatronics & Human-Machine Control)

Raymund ten Broek (Urbansports Performance Centre)

Eline van der Kruk (TU Delft - Biomechatronics & Human-Machine Control)

Jason K. Moore (TU Delft - Biomechatronics & Human-Machine Control)

Research Group
Biomechatronics & Human-Machine Control
Copyright
© 2024 Jan T. Heinen, S.G. Brockie, Raymund ten Broek, E. van der Kruk, J.K. Moore
To reference this document use:
https://doi.org/10.1007/s12283-023-00448-y
More Info
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Publication Year
2024
Language
English
Copyright
© 2024 Jan T. Heinen, S.G. Brockie, Raymund ten Broek, E. van der Kruk, J.K. Moore
Research Group
Biomechatronics & Human-Machine Control
Issue number
1
Volume number
27
DOI:
https://doi.org/10.1007/s12283-023-00448-y
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Abstract

The ollie is the base aerial human–board maneuver, foundational to most modern skateboarding tricks. We formulate and solve an optimal control problem of a two-dimensional simplified human model and a rigid body skateboard with the objective of maximizing the height of the ollie. Our solution simultaneously discovers realistic human-applied force trajectories and optimal board geometry. We accomplish this with a direct collocation formulation using a null seed initial guess by carefully modeling the discontinuous aspects of board–ground impact and foot–board friction. This leads to efficient and robust solutions that are 10 times more computationally efficient than prior work on similar problems. The solutions show that ollie height can increase 3% by decreasing the wheelbase and that a smaller board with a back-foot-dominated force strategy can give 12% higher ollies. Our model can be used to inform jump strategy and the effects of changes to the essential board geometry.