# Computationally-Robust and Efficient Prioritized Whole-Body Controller with Contact Constraints

arXiv: https://arxiv.org/abs/1807.01222 · HTML: https://mlsanity.com/paper/1807.01222/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jul 2018.

## Built on by (most cited first, 3 of 3)

- [Learning to Jump from Pixels](https://mlsanity.com/paper/2110.15344/) (2021)
- [ADP: Adversarial Dynamics Priors for Physically Grounded Humanoid Locomotion](https://mlsanity.com/paper/2607.03454/) (2026)
- [Any2Any: Efficient Cross-Embodiment Transfer for Humanoid Whole-Body Tracking](https://mlsanity.com/paper/2605.23733/) (2026)

## Abstract (arXiv)

In this paper, we devise methods for the multi- objective control of humanoid robots, a.k.a. prioritized whole- body controllers, that achieve efficiency and robustness in the algorithmic computations. We use a form of whole-body controllers that is very general via incorporating centroidal momentum dynamics, operational task priorities, contact re- action forces, and internal force constraints. First, we achieve efficiency by solving a quadratic program that only involves the floating base dynamics and the reaction forces. Second, we achieve computational robustness by relaxing task accelerations such that they comply with friction cone constraints. Finally, we incorporate methods for smooth contact transitions to enhance the control of dynamic locomotion behaviors. The proposed methods are demonstrated both in simulation and in real experiments using a passive-ankle bipedal robot.