7 citations · 16 across the 11 of their papers we have counts for
11 papers
Real-Time Learning of Predictive Dynamic Obstacle Models for Robotic Motion Planning
Stella Kombo, Masih Haseli, Skylar X. Wei +1
Autonomous systems often must predict the motions of nearby agents from partial and noisy data. This paper asks and answers the question: "can we learn, in real-time, a nonlinear p…
A Safety-Critical Framework for UGVs in Complex Environments: A Data-Driven Discrepancy-Aware Approach
Skylar X. Wei, Lu Gan, Joel W. Burdick
This work presents a novel data-driven multi-layered planning and control framework for the safe navigation of a class of unmanned ground vehicles (UGVs) in the presence of unknown…
A Learning-Based Framework for Safe Human-Robot Collaboration with Multiple Backup Control Barrier Functions
Neil C. Janwani, Ersin Daş, Thomas Touma +3
Ensuring robot safety in complex environments is a difficult task due to actuation limits, such as torque bounds. This paper presents a safety-critical control framework that lever…
Robust Control Barrier Functions with Uncertainty Estimation
Ersin Daş, Skylar X. Wei, Joel W. Burdick
This paper proposes a safety controller for control-affine nonlinear systems with unmodelled dynamics and disturbances to improve closed-loop robustness. Uncertainty estimation-bas…
Learning Disturbances Online for Risk-Aware Control: Risk-Aware Flight with Less Than One Minute of Data
Prithvi Akella, Skylar X. Wei, Joel W. Burdick +1
Recent advances in safety-critical risk-aware control are predicated on apriori knowledge of the disturbances a system might face. This paper proposes a method to efficiently learn…
Adaptive Conformal Prediction for Motion Planning among Dynamic Agents
Anushri Dixit, Lars Lindemann, Skylar Wei +3
This paper proposes an algorithm for motion planning among dynamic agents using adaptive conformal prediction. We consider a deterministic control system and use trajectory predict…
Moving Obstacle Avoidance: a Data-Driven Risk-Aware Approach
Skylar X. Wei, Anushri Dixit, Shashank Tomar +1
This paper proposes a new structured method for a moving agent to predict the paths of dynamically moving obstacles and avoid them using a risk-aware model predictive control (MPC)…
Differential Flatness and Flatness Inspired Control of Aerial Manipulators based on Lagrangian Reduction
Skylar X. Wei, Peder Harderup, Joel Burdick
This paper shows that the dynamics of a general class of aerial manipulators, consist of an underactuated multi-rotor base with an arbitrary k-linked articulated manipulator, are d…
Quadrotor Trajectory Tracking with Learned Dynamics: Joint Koopman-based Learning of System Models and Function Dictionaries
Carl Folkestad, Skylar X. Wei, Joel W. Burdick
Nonlinear dynamical effects are crucial to the operation of many agile robotic systems. Koopman-based model learning methods can capture these nonlinear dynamical system effects in…
Nonlinear Controllability Assessment of Aerial Manipulator Systems using Lagrangian Reduction
Skylar X. Wei, Matthew R. Burkhardt, Joel Burdick
This paper analyzes the nonlinear Small-Time Local Controllability (STLC) of a class of underatuated aerial manipulator robots. We apply methods of Lagrangian reduction to obtain t…
Motivations and Preliminary Design for Mid-Air Deployment of a Science Rotorcraft on Mars
Jeff Delaune, Jacob Izraelevitz, Larry A. Young +18
Mid-Air Deployment (MAD) of a rotorcraft during Entry, Descent and Landing (EDL) on Mars eliminates the need to carry a propulsion or airbag landing system. This reduces the total…