# Stair Climbing Stabilization of the HRP-4 Humanoid Robot using Whole-body Admittance Control

arXiv: https://arxiv.org/abs/1809.07073 · HTML: https://mlsanity.com/paper/1809.07073/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Sep 2018.

## Built on by (most cited first, 9 of 9)

- [Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control](https://mlsanity.com/paper/2401.16889/) (2024)
- [Learning Bipedal Walking for Humanoids with Current Feedback](https://mlsanity.com/paper/2303.03724/) (2023)
- [Learning Bipedal Walking On Planned Footsteps For Humanoid Robots](https://mlsanity.com/paper/2207.12644/) (2022)
- [Robust Humanoid Walking on Compliant and Uneven Terrain with Deep Reinforcement Learning](https://mlsanity.com/paper/2504.13619/) (2025)
- [Robust Contact State Estimation in Humanoid Walking Gaits](https://mlsanity.com/paper/2208.00278/) (2022)
- [Learning Bipedal Walking for Humanoid Robots in Challenging Environments with Obstacle Avoidance](https://mlsanity.com/paper/2410.08212/) (2024)
- [Learning Generic and Dynamic Locomotion of Humanoids Across Discrete Terrains](https://mlsanity.com/paper/2405.17227/) (2024)
- [Words2Contact: Identifying Support Contacts from Verbal Instructions Using Foundation Models](https://mlsanity.com/paper/2407.14229/) (2024)
- [Real-Time Polygonal Semantic Mapping for Humanoid Robot Stair Climbing](https://mlsanity.com/paper/2411.01919/) (2024)

## Abstract (arXiv)

We consider dynamic stair climbing with the HRP-4 humanoid robot as part of an Airbus manufacturing use-case demonstrator. We share experimental knowledge gathered so as to achieve this task, which HRP-4 had never been challenged to before. In particular, we extend walkingstabilization based on linear inverted pendulum tracking by quadratic programming-based wrench distribution and a whole-body admittance controller that applies both end-effector and CoM strategies. While existing stabilizers tend to use either one or the other, our experience suggests that the combination of these two approaches improves tracking performance. We demonstrate this solution in an on-site experiment where HRP-4 climbs an industrial staircase with 18.5 cm high steps, and release our walking controller as open source software.