33 citations · 64 across the 13 of their papers we have counts for
14 papers
Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running
Devin Crowley, Jeremy Dao, Helei Duan +3
In this paper, we explore the space of running gaits for the bipedal robot Cassie. Our first contribution is to present an approach for optimizing gait efficiency across a spectrum…
Dynamic Bipedal Maneuvers through Sim-to-Real Reinforcement Learning
Fangzhou Yu, Ryan Batke, Jeremy Dao +3
For legged robots to match the athletic capabilities of humans and animals, they must not only produce robust periodic walking and running, but also seamlessly switch between nomin…
Optimizing Bipedal Maneuvers of Single Rigid-Body Models for Reinforcement Learning
Ryan Batke, Fangzhou Yu, Jeremy Dao +4
In this work, we propose a method to generate reduced-order model reference trajectories for general classes of highly dynamic maneuvers for bipedal robots for use in sim-to-real r…
Sim-to-Real Learning for Bipedal Locomotion Under Unsensed Dynamic Loads
Jeremy Dao, Kevin Green, Helei Duan +2
Recent work on sim-to-real learning for bipedal locomotion has demonstrated new levels of robustness and agility over a variety of terrains. However, that work, and most prior bipe…
Motion Planning for Agile Legged Locomotion using Failure Margin Constraints
Kevin Green, John Warila, Ross L. Hatton +1
The complex dynamics of agile robotic legged locomotion requires motion planning to intelligently adjust footstep locations. Often, bipedal footstep and motion planning use mathema…
Sim-to-Real Learning of Footstep-Constrained Bipedal Dynamic Walking
Helei Duan, Ashish Malik, Jeremy Dao +5
Recently, work on reinforcement learning (RL) for bipedal robots has successfully learned controllers for a variety of dynamic gaits with robust sim-to-real demonstrations. In orde…
Ankle Torque During Mid-Stance Does Not Lower Energy Requirements of Steady Gaits
Mike Hector, Kevin Green, Burak Sencer +1
In this paper, we investigate whether applying ankle torques during mid-stance can be a more effective way to reduce energetic cost of locomotion than actuating leg length alone. A…
Design and Control of a Recovery System for Legged Robots
Kevin Green, Nils Smit-Anseeuw, Rodney Gleason +1
This paper describes the design and control of a support and recovery system for use with planar legged robots. The system operates in three modes. First, it can be operated in a f…
Blind Bipedal Stair Traversal via Sim-to-Real Reinforcement Learning
Jonah Siekmann, Kevin Green, John Warila +2
Accurate and precise terrain estimation is a difficult problem for robot locomotion in real-world environments. Thus, it is useful to have systems that do not depend on accurate es…
Learning Task Space Actions for Bipedal Locomotion
Helei Duan, Jeremy Dao, Kevin Green +3
Recent work has demonstrated the success of reinforcement learning (RL) for training bipedal locomotion policies for real robots. This prior work, however, has focused on learning…
Learning Spring Mass Locomotion: Guiding Policies with a Reduced-Order Model
Kevin Green, Yesh Godse, Jeremy Dao +3
In this paper, we describe an approach to achieve dynamic legged locomotion on physical robots which combines existing methods for control with reinforcement learning. Specifically…
Planning for the Unexpected: Explicitly Optimizing Motions for Ground Uncertainty in Running
Kevin Green, Ross L. Hatton, Jonathan Hurst
We propose a method to generate actuation plans for a reduced order, dynamic model of bipedal running. This method explicitly enforces robustness to ground uncertainty. The plan ge…
Periodic solutions to a mean-field model for electrocortical activity
Lennaert van Veen, Kevin Green
We consider a continuum model of electrical signals in the human cortex, which takes the form of a system of semilinear, hyperbolic partial differential equations for the inhibitor…
Open-source tools for dynamical analysis of Liley's mean-field cortex model
Kevin R. Green, Lennaert van Veen
Mean-field models of the mammalian cortex treat this part of the brain as a two-dimensional excitable medium. The electrical potentials, generated by the excitatory and inhibitory…