# Inverse Dynamics Control of Compliant Hybrid Zero Dynamic Walking

arXiv: https://arxiv.org/abs/2010.09047 · HTML: https://mlsanity.com/paper/2010.09047/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Oct 2020.

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

- [Robust Humanoid Walking on Compliant and Uneven Terrain with Deep Reinforcement Learning](https://mlsanity.com/paper/2504.13619/) (2025)
- [HybridMimic: Hybrid RL-Centroidal Control for Humanoid Motion Mimicking](https://mlsanity.com/paper/2603.06775/) (2026)
- [Model-Informed Safe Reinforcement Learning for Bipedal Locomotion via Step-to-Step Prediction](https://mlsanity.com/paper/2609.34486/) (2026)

## Abstract (arXiv)

We present a trajectory planning and control architecture for bipedal locomotion at a variety of speeds on a highly underactuated and compliant bipedal robot. A library of compliant walking trajectories are planned offline, and stored as compact arrays of polynomial coefficients for tracking online. The control implementation uses a floating-base inverse dynamics controller which generates dynamically consistent feedforward torques to realize walking using information obtained from the trajectory optimization. The effectiveness of the controller is demonstrated in simulation and on hardware for walking both indoors on flat terrain and over unplanned disturbances outdoors. Additionally, both the controller and optimization source code are made available on GitHub.