129 citations · 340 across the 16 of their papers we have counts for
17 papers
Active Learning of Dynamics for Data-Driven Control Using Koopman Operators
Ian Abraham, Todd D. Murphey
This paper presents an active learning strategy for robotic systems that takes into account task information, enables fast learning, and allows control to be readily synthesized by…
Highly Parallelized Data-driven MPC for Minimal Intervention Shared Control
Alexander Broad, Todd Murphey, Brenna Argall
We present a shared control paradigm that improves a user's ability to operate complex, dynamic systems in potentially dangerous environments without a priori knowledge of the user…
Operation and Imitation under Safety-Aware Shared Control
Alexander Broad, Todd Murphey, Brenna Argall
We describe a shared control methodology that can, without knowledge of the task, be used to improve a human's control of a dynamic system, be used as a training mechanism, and be…
Efficient Computation of Higher-Order Variational Integrators in Robotic Simulation and Trajectory Optimization
Taosha Fan, Jarvis Schultz, Todd Murphey
This paper addresses the problem of efficiently computing higher-order variational integrators in simulation and trajectory optimization of mechanical systems as those often found…
On the Benefits of Surrogate Lagrangians in Optimal Control and Planning Algorithms
Gerardo De La Torre, Todd Murphey
This paper explores the relationship between numerical integrators and optimal control algorithms. Specifically, the performance of the differential dynamical programming (DDP) alg…
Dynamic Task Execution using Active Parameter Identification with the Baxter Research Robot
Andrew D. Wilson, Jarvis A. Schultz, Alex R. Ansari +1
This paper presents experimental results from real-time parameter estimation of a system model and subsequent trajectory optimization for a dynamic task using the Baxter Research R…