# Dynamic Walking with Compliance on a Cassie Bipedal Robot

arXiv: https://arxiv.org/abs/1904.11104 · HTML: https://mlsanity.com/paper/1904.11104/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Apr 2019.

## Built on by (most cited first, 5 of 5)

- [Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning](https://mlsanity.com/paper/2408.14472/) (2024)
- [OstrichRL: A Musculoskeletal Ostrich Simulation to Study Bio-mechanical Locomotion](https://mlsanity.com/paper/2112.06061/) (2021)
- [Olaf: Bringing an Animated Character to Life in the Physical World](https://mlsanity.com/paper/2512.16705/) (2025)
- [NaviGait: Navigating Dynamically Feasible Gait Libraries using Deep Reinforcement Learning](https://mlsanity.com/paper/2510.11542/) (2025)
- [Teacher Motion Priors: Enhancing Robot Locomotion over Challenging Terrain](https://mlsanity.com/paper/2504.10390/) (2025)

## Abstract (arXiv)

The control of bipedal robotic walking remains a challenging problem in the domains of computation and experiment, due to the multi-body dynamics and various sources of uncertainty. In recent years, there has been a rising trend towards model reduction and the design of intuitive controllers to overcome the gap between assumed model and reality. Despite its viability in practical implementation, this local representation of true dynamics naturally indicate limited scalibility towards more dynamical behaviors. With the goal of moving towards increasingly dynamic behaviors, we leverage the detailed full body dynamics to generate controllers for the robotic system which utilizes compliant elements in the passive dynamics. In this process, we present a feasible computation method that yields walking trajectories for a highly complex robotic system. Direct implementation of these results on physical hardware is also performed with minimal tuning and heuristics. We validate the suggested method by applying a consistent control scheme across simulation, optimization and experiment, the result is that the bipedal robot Cassie walks over a variety of indoor and outdoor terrains reliably.