A unified framework for walking and running of bipedal robots
Not on the map. Why?
Abstract (arXiv)
In this paper, we propose a novel framework capable of generating various walking and running gaits for bipedal robots. The main goal is to relax the fixed center of mass (CoM) height assumption of the linear inverted pendulum model (LIPM) and generate a wider range of walking and running motions, without a considerable increase in complexity. To do so, we use the concept of virtual constraints in the centroidal space which enables generating motions beyond walking while keeping the complexity at a minimum. By a proper choice of these virtual constraints, we show that we can generate different types of walking and running motions. More importantly, enforcing the virtual constraints through feedback renders the dynamics linear and enables us to design a feedback control mechanism which adapts the next step location and timing in face of disturbances, through a simple quadratic program (QP). To show the effectiveness of this framework, we showcase different walking and running simulations of the biped robot Bolt in the presence of both environmental uncertainties and external disturbances.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Oct 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 2; 2025: 1.
3 papers.
- 2024Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Controlcited by 99
- 2024Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recoverycited by 5
- 2025Constrained Reinforcement Learning for Unstable Point-Feet Bipedal Locomotion Applied to the Bolt Robotcited by 1
- 2025Constrained Reinforcement Learning for Unstable Point-Feet Bipedal Locomotion Applied to the Bolt Robot4 Aug 2025
- 2024Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery10 Dec 2024
- 2024Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control30 Jan 2024