283 citations · 355 across the 9 of their papers we have counts for
10 papers
A Data-Driven Approach to Geometric Modeling of Systems with Low-Bandwidth Actuator Dynamics
Siming Deng, Junning Liu, Bibekananda Datta +5
It is challenging to perform system identification on soft robots due to their underactuated, high-dimensional dynamics. In this work, we present a data-driven modeling framework,…
An observability result related to active sensing
Eduardo D. Sontag, Debojyoti Biswas, Noah J. Cowan
For a general class of translationally invariant systems with a specific category of nonlinearity in the output, this paper presents necessary and sufficient conditions for global…
Optimal Estimation with Sensor Delay
Di Cao, Noah J. Cowan, James S. Freudenberg
Given a plant subject to delayed sensor measurement, there are several approaches to compensate for the delay. An obvious approach is to address this problem in state space, where…
Prospective Learning: Principled Extrapolation to the Future
Ashwin De Silva, Rahul Ramesh, Lyle Ungar +40
Learning is a process which can update decision rules, based on past experience, such that future performance improves. Traditionally, machine learning is often evaluated under the…
Identification of a Hybrid Spring Mass Damper via Harmonic Transfer Functions as a Step Towards Data-Driven Models for Legged Locomotion
İsmail Uyanık, Mustafa Mert Ankaralı, Noah J. Cowan +2
There are limitations on the extent to which manually constructed mathematical models can capture relevant aspects of legged locomotion. Even simple models for basic behaviors such…
Walking dynamics are symmetric (enough)
M. Mert Ankaralı, Shahin Sefati, Manu S. Madhav +3
Many biological phenomena such as locomotion, circadian cycles, and breathing are rhythmic in nature and can be modeled as rhythmic dynamical systems. Dynamical systems modeling of…
Feedback Control as a Framework for Understanding Tradeoffs in Biology
Noah J. Cowan, Mustafa Mert Ankarali, Jonathan P. Dyhr +7
Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathem…
Optimal Control with Noisy Time
Andrew Lamperski, Noah J. Cowan
This paper examines stochastic optimal control problems in which the state is perfectly known, but the controller's measure of time is a stochastic process derived from a strictly…
Efficient Gradient Estimation for Motor Control Learning
Gregory Lawrence, Noah Cowan, Stuart Russell
The task of estimating the gradient of a function in the presence of noise is central to several forms of reinforcement learning, including policy search methods. We present two te…
Nodal dynamics, not degree distributions, determine the structural controllability of complex networks
Noah J. Cowan, Erick J. Chastain, Daril A. Vilhena +2
Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical a…