Learning robot gait stability using neural networks as sensory feedback function for Central Pattern Generators

By Sébastien Gay, José Santos-Victor, Auke Jan Ijspeert. 2013

72 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Biomedical Engineering, Ecology, Evolution, Behavior and Systematics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Erwin Coumans
2. Jie Tan
3. Vincent Vanhoucke
4. Ken Caluwaerts
5. Tingnan Zhang
6. Yunfei Bai

In Biomedical Engineering

1. Jie Tan
2. Tingnan Zhang
3. Vikas Sindhwani
4. Atil Iscen
5. Erwin Coumans
6. Benjamin Schrauwen
7. Vincent Vanhoucke
8. Ken Caluwaerts

In Ecology, Evolution, Behavior and Systematics

1. Jie Tan

Citations in the corpus

• Sim-to-Real: Learning Agile Locomotion For Quadruped Robots (2018, background): “[13] learned a neural network that modified a Central Pattern Generator controller for stable quadruped locomotion.”
• Design and control of compliant tensegrity robots through simulation and hardware validation (2014, methodology): “[37], where sensory information is preprocessed by a neural network and trained using particle-swarm optimization methods before being fed back to the CPG.”
• Policies Modulating Trajectory Generators (2018, background): “[15] learned a neural network that modulated a CPG.”