activity
20202023
most citedFlexible Supervised Autonomy for Exploration in Subterranean Environments

18 citations · 20 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2023

A Population-Level Analysis of Neural Dynamics in Robust Legged Robots

Eugene R. Rush, Christoffer Heckman, Kaushik Jayaram +1

Recurrent neural network-based reinforcement learning systems are capable of complex motor control tasks such as locomotion and manipulation, however, much of their underlying mech…

q-bio.NC2023★ 2 cited

From Data-Fitting to Discovery: Interpreting the Neural Dynamics of Motor Control through Reinforcement Learning

Eugene R. Rush, Kaushik Jayaram, J. Sean Humbert

In motor neuroscience, artificial recurrent neural networks models often complement animal studies. However, most modeling efforts are limited to data-fitting, and the few that exa…

cs.RO2023★ 18 cited

Flexible Supervised Autonomy for Exploration in Subterranean Environments

Harel Biggie, Eugene R. Rush, Danny G. Riley +9

While the capabilities of autonomous systems have been steadily improving in recent years, these systems still struggle to rapidly explore previously unknown environments without t…

cs.RO2021

Multi-Agent Autonomy: Advancements and Challenges in Subterranean Exploration

Michael T. Ohradzansky, Eugene R. Rush, Danny G. Riley +9

Artificial intelligence has undergone immense growth and maturation in recent years, though autonomous systems have traditionally struggled when fielded in diverse and previously u…

cs.RO2021

3D Reactive Control and Frontier-Based Exploration for Unstructured Environments

Shakeeb Ahmad, Andrew B. Mills, Eugene R. Rush +2

The paper proposes a reliable and robust planning solution to the long range robotic navigation problem in extremely cluttered environments. A two-layer planning architecture is pr…

cs.RO2020

APF-PF: Probabilistic Depth Perception for 3D Reactive Obstacle Avoidance

Shakeeb Ahmad, Zachary N. Sunberg, J. Sean Humbert

This paper proposes a framework for 3D obstacle avoidance in the presence of partial observability of environment obstacles. The method focuses on the utility of the Artificial Pot…

physics.app-ph2020

Miniaturized Circuitry for Capacitive Self-sensing and Closed-loop Control of Soft Electrostatic Transducers

Khoi Ly, Nicholas Kellaris, Dade McMorris +8

Soft robotics is a field of robotic system design characterized by materials and structures that exhibit large-scale deformation, high compliance, and rich multifunctionality. The…