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ManyQuadrupeds: Learning a Single Locomotion Policy for Diverse Quadruped Robots
Learning a locomotion policy for quadruped robots has traditionally been constrained to a specific robot morphology, mass, and size.
DeepTransition: Viability Leads to the Emergence of Gait Transitions in Learning Anticipatory Quadrupedal Locomotion Skills
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.
Puppeteer and Marionette: Learning Anticipatory Quadrupedal Locomotion Based on Interactions of a Central Pattern Generator and Supraspinal Drive
Moreover, our investigation shows that sensing the front feet distances to the gap is the most important and sufficient sensory information for learning gap crossing.
Visual CPG-RL: Learning Central Pattern Generators for Visually-Guided Quadruped Locomotion
2) What are the effects of using a memory-enabled vs. a memory-free policy network with respect to robustness, energy-efficiency, and tracking performance in sim-to-real navigation tasks?
CPG-RL: Learning Central Pattern Generators for Quadruped Locomotion
In this letter, we present a method for integrating central pattern generators (CPGs), i. e. systems of coupled oscillators, into the deep reinforcement learning (DRL) framework to produce robust and omnidirectional quadruped locomotion.
A Spiking Central Pattern Generator for the control of a simulated lamprey robot running on SpiNNaker and Loihi neuromorphic boards
In this work we propose a spiking CPG neural network and its implementation on neuromorphic hardware as a means to control a simulated lamprey model.
