Abstract
Studies of computationally and analytically convenient approximations of rigid body dynamics have brought valuable insight into the field of humanoid robotics. Additionally, they facilitate the design of effective walking pattern generators. Going further than the classical Zero Moment Point-based methods, this paper presents two simple and novel approaches to solve for 3D locomotion with multiple non-coplanar contacts. Both formulations use model predictive control to generate dynamically balanced trajectories with no restrictions on the center of mass height trajectory. The first formulation treats the balance criterion as an objective function, and solves the control problem using a sequence of alternating convex quadratic programs. The second formulation considers the criterion as constraints, and solves a succession of convex quadratically constrained quadratic programs.
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The research presented in this paper was partially funded by the ROMEO2 project.
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Perrin, N., Lau, D., Padois, V. (2018). Effective Generation of Dynamically Balanced Locomotion with Multiple Non-coplanar Contacts. In: Bicchi, A., Burgard, W. (eds) Robotics Research. Springer Proceedings in Advanced Robotics, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-319-60916-4_12
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DOI: https://doi.org/10.1007/978-3-319-60916-4_12
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