@article{escande_hierarchical_2014,
	title = {Hierarchical quadratic programming: {Fast} online humanoid-robot motion generation},
	volume = {33},
	issn = {0278-3649},
	shorttitle = {Hierarchical quadratic programming},
	url = {https://doi.org/10.1177/0278364914521306},
	doi = {10.1177/0278364914521306},
	abstract = {Hierarchical least-square optimization is often used in robotics to inverse a direct function when multiple incompatible objectives are involved. Typical examples are inverse kinematics or dynamics. The objectives can be given as equalities to be satisfied (e.g. point-to-point task) or as areas of satisfaction (e.g. the joint range). This paper proposes a complete solution to solve multiple least-square quadratic problems of both equality and inequality constraints ordered into a strict hierarchy. Our method is able to solve a hierarchy of only equalities 10 times faster than the iterative-projection hierarchical solvers and can consider inequalities at any level while running at the typical control frequency on whole-body size problems. This generic solver is used to resolve the redundancy of humanoid robots while generating complex movements in constrained environments.},
	number = {7},
	urldate = {2021-12-01},
	journal = {The International Journal of Robotics Research},
	author = {Escande, Adrien and Mansard, Nicolas and Wieber, Pierre-Brice},
	month = jun,
	year = {2014},
	note = {Publisher: SAGE Publications Ltd STM},
	pages = {1006--1028},
}

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