ArticleNature communications2024
Viability leads to the emergence of gait transitions in learning agile quadrupedal locomotion on challenging terrains.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 26 citations in OpenAlex.
- Terrain-Height-Blind Quadrupedal Locomotion Through Privileged Teacher-Student Learning and a Shared Gait-Structured Central Pattern Generator.Biomimetics (Basel, Switzerland) · 2026Article
- Influence of Longitudinal Center of Mass Position on Load Distribution in High-Speed Quadrupedal Locomotion.Biomimetics (Basel, Switzerland) · 2026Article
- Synergy of postural adaptation and exteroception for robust CPG-driven quadrupedal locomotion.Scientific reports · 2026Article
- Gait Optimization Control of Spinal Quadruped Robot Based on Deep Reinforcement Learning.Sensors (Basel, Switzerland) · 2026Article
- Article
- AI-driven quadruped robots: from fundamental locomotion to advanced biomimetic behaviors.Frontiers in neurorobotics · 2026Review
- Discovery of skill-switching criteria for learning agile quadruped locomotion.Frontiers in robotics and AI · 2026Article
- Enhancing Legged Robot Locomotion Through Smooth Transitions Using Spiking Central Pattern Generators.Biomimetics (Basel, Switzerland) · 2025Article
- Hierarchical reinforcement learning with central pattern generator for enabling a quadruped robot simulator to walk on a variety of terrains.Scientific reports · 2025Article
- Foot trajectory as a key factor for diverse gait patterns in quadruped robot locomotion.Scientific reports · 2025Article
- Analysis of impact of limb segment length variations during reinforcement learning in four-legged robot.Scientific reports · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Quadruped animals are capable of seamless transitions between different gaits. While energy efficiency appears to be one of the reasons for changing gaits, other determinant factors likely play a role too, including terrain properties. In this article, we propose that viability, i.e., the avoidance of falls, represents an important criterion for gait transitions. We investigate the emergence of gait transitions through the interaction between supraspinal drive (brain), the central pattern generator in the spinal cord, the body, and exteroceptive sensing by leveraging deep reinforcement learning and robotics tools. Consistent with quadruped animal data, we show that the walk-trot gait transition for quadruped robots on flat terrain improves both viability and energy efficiency. Furthermore, we investigate the effects of discrete terrain (i.e., crossing successive gaps) on imposing gait transitions, and find the emergence of trot-pronk transitions to avoid non-viable states. Viability is the only improved factor after gait transitions on both flat and discrete gap terrains, suggesting that viability could be a primary and universal objective of gait transitions, while other criteria are secondary objectives and/or a consequence of viability. Moreover, our experiments demonstrate state-of-the-art quadruped robot agility in challenging scenarios.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.