47 citations · 57 across the 14 of their papers we have counts for
14 papers
Fauna Sprout: A lightweight, approachable, developer-ready humanoid robot
Fauna Robotics, :, Diego Aldarondo +48
Recent advances in learned control, large-scale simulation, and generative models have accelerated progress toward general-purpose robotic controllers, yet the field still lacks pl…
Safe Dynamic Motion Generation in Configuration Space Using Differentiable Distance Fields
Xuemin Chi, Yiming Li, Jihao Huang +3
Generating collision-free motions in dynamic environments is a challenging problem for high-dimensional robotics, particularly under real-time constraints. Control Barrier Function…
Sailing Through Point Clouds: Safe Navigation Using Point Cloud Based Control Barrier Functions
Bolun Dai, Rooholla Khorrambakht, Prashanth Krishnamurthy +1
The capability to navigate safely in an unstructured environment is crucial when deploying robotic systems in real-world scenarios. Recently, control barrier function (CBF) based a…
Learning a Better Control Barrier Function Under Uncertain Dynamics
Bolun Dai, Prashanth Krishnamurthy, Farshad Khorrami
Using control barrier functions (CBFs) as safety filters provides a computationally inexpensive yet effective method for constructing controllers in safety-critical applications. H…
Differentiable Optimization Based Time-Varying Control Barrier Functions for Dynamic Obstacle Avoidance
Bolun Dai, Rooholla Khorrambakht, Prashanth Krishnamurthy +1
Control barrier functions (CBFs) provide a simple yet effective way for safe control synthesis. Recently, work has been done using differentiable optimization (diffOpt) based metho…
Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks
Maxime Chevalier-Boisvert, Bolun Dai, Mark Towers +6
We present the Minigrid and Miniworld libraries which provide a suite of goal-oriented 2D and 3D environments. The libraries were explicitly created with a minimalistic design para…
State Constrained Stochastic Optimal Control for Continuous and Hybrid Dynamical Systems Using DFBSDE
Bolun Dai, Prashanth Krishnamurthy, Andrew Papanicolaou +1
We develop a computationally efficient learning-based forward-backward stochastic differential equations (FBSDE) controller for both continuous and hybrid dynamical (HD) systems su…
Safe Navigation and Obstacle Avoidance Using Differentiable Optimization Based Control Barrier Functions
Bolun Dai, Rooholla Khorrambakht, Prashanth Krishnamurthy +3
Control barrier functions (CBFs) have been widely applied to safety-critical robotic applications. However, the construction of control barrier functions for robotic systems remain…
Data-Efficient Control Barrier Function Refinement
Bolun Dai, Heming Huang, Prashanth Krishnamurthy +1
Control barrier functions (CBFs) have been widely used for synthesizing controllers in safety-critical applications. When used as a safety filter, it provides a simple and computat…
Learning a Better Control Barrier Function
Bolun Dai, Prashanth Krishnamurthy, Farshad Khorrami
Control barrier functions (CBFs) are widely used in safety-critical controllers. However, constructing a valid CBF is challenging, especially under nonlinear or non-convex constrai…
Adaptive Identification of Legged Robotic Kinematic Structure
Bolun Dai
Model-based control usually relies on an accurate model, which is often obtained from CAD and actuator models. The more accurate the model the better the control performance. Howev…
Learning Locomotion Controllers for Walking Using Deep FBSDE
Bolun Dai, Virinchi Roy Surabhi, Prashanth Krishnamurthy +1
In this paper, we propose a deep forward-backward stochastic differential equation (FBSDE) based control algorithm for locomotion tasks. We also include state constraints in the FB…
State Constrained Stochastic Optimal Control Using LSTMs
Bolun Dai, Prashanth Krishnamurthy, Andrew Papanicolaou +1
In this paper, we propose a new methodology for state constrained stochastic optimal control (SOC) problems. The solution is based on past work in solving SOC problems using forwar…
GRP Model for Sensorimotor Learning
Tianyu Li, Bolun Dai
Learning from complex demonstrations is challenging, especially when the demonstration consists of different strategies. A popular approach is to use a deep neural network to perfo…