14 papers
Generate, Track, Improve: Perceptive Multi-Skill Humanoid Locomotion with RL-Fine-Tuned Motion Generators
Zachary Olkin, William D. Compton, Aaron D. Ames
General purpose humanoids require locomotion controllers that are multi-skill, perceptive, dynamic, and robust enough to go anywhere humans can. In this work, we present a two laye…
Learning Safe Humanoid Navigation from Reduced Order Models
William D. Compton, Zachary Olkin, Ryan Bena +1
Research in humanoid robotics has achieved rapid progress in locomotion, and recent results have pushed the boundary on autonomous navigation. We demonstrate that a standard single…
Terrain Consistent Reference-Guided RL for Humanoid Navigation Autonomy
William D. Compton, Zachary Olkin, Aaron D. Ames
We present a method for training reference-guided, perceptive reinforcement learning locomotion policies for humanoid robots in which reference trajectories are modulated in traini…
Stability of Control Lyapunov Function Guided Reinforcement Learning
Zachary Olkin, William D. Compton, Aaron D. Ames
Reinforcement learning (RL) has become the de facto method for achieving locomotion on humanoid robots in practice, yet stability analysis of the corresponding control policies is…
Decoding Defensive Coverage Responsibilities in American Football Using Factorized Attention Based Transformer Models
Kevin Song, Evan Diewald, Ornob Siddiquee +4
Defensive coverage schemes in the National Football League (NFL) represent complex tactical patterns requiring coordinated assignments among defenders who must react dynamically to…
Walk the PLANC: Physics-Guided RL for Agile Humanoid Locomotion on Constrained Footholds
Min Dai, William D. Compton, Junheng Li +2
Bipedal humanoid robots must precisely coordinate balance, timing, and contact decisions when locomoting on constrained footholds such as stepping stones, beams, and planks -- even…
Chasing Stability: Humanoid Running via Control Lyapunov Function Guided Reinforcement Learning
Zachary Olkin, Kejun Li, William D. Compton +1
Achieving highly dynamic behaviors on humanoid robots, such as running, requires controllers that are both robust and precise, and hence difficult to design. Classical control meth…
Learning for Layered Safety-Critical Control with Predictive Control Barrier Functions
William D. Compton, Max H. Cohen, Aaron D. Ames
Safety filters leveraging control barrier functions (CBFs) are highly effective for enforcing safe behavior on complex systems. It is often easier to synthesize CBFs for a Reduced…
Safety-Critical Controller Synthesis with Reduced-Order Models
Max H. Cohen, Noel Csomay-Shanklin, William D. Compton +2
Reduced-order models (ROMs) provide lower dimensional representations of complex systems, capturing their salient features while simplifying control design. Building on previous wo…
Dynamic Tube MPC: Learning Tube Dynamics with Massively Parallel Simulation for Robust Safety in Practice
William D. Compton, Noel Csomay-Shanklin, Cole Johnson +1
Safe navigation of cluttered environments is a critical challenge in robotics. It is typically approached by separating the planning and tracking problems, with planning executed o…
Dynamically Feasible Path Planning in Cluttered Environments via Reachable Bezier Polytopes
Noel Csomay-Shanklin, William D. Compton, Aaron D. Ames
The deployment of robotic systems in real world environments requires the ability to quickly produce paths through cluttered, non-convex spaces. These planned trajectories must be…
A Contract Theory for Layered Control Architectures
Manuel Mazo, Will Compton, Max H. Cohen +1
Autonomous systems typically leverage layered control architectures with a combination of discrete and continuous models operating at different timescales. As a result, layered sys…
Robust Agility via Learned Zero Dynamics Policies
Noel Csomay-Shanklin, William D. Compton, Ivan Dario Jimenez Rodriguez +3
We study the design of robust and agile controllers for hybrid underactuated systems. Our approach breaks down the task of creating a stabilizing controller into: 1) learning a map…
Constructive Nonlinear Control of Underactuated Systems via Zero Dynamics Policies
William Compton, Ivan Dario Jimenez Rodriguez, Noel Csomay-Shanklin +2
Stabilizing underactuated systems is an inherently challenging control task due to fundamental limitations on how the control input affects the unactuated dynamics. Decomposing the…