62 citations · 280 across the 51 of their papers we have counts for
6 papers · 1 filter
Towards Tenodesis-Modulated Control of an Assistive Hand Exoskeleton for SCI
Joaquin Palacios, Alexandra Deli-Ivanov, Ava Chen +4
Restoration of hand function is one of the highest priorities for SCI populations. In this work, we present a prototype of a robotic assistive orthosis capable of implementing teno…
An Investigation of Multi-feature Extraction and Super-resolution with Fast Microphone Arrays
Eric T. Chang, Runsheng Wang, Peter Ballentine +5
In this work, we use MEMS microphones as vibration sensors to simultaneously classify texture and estimate contact position and velocity. Vibration sensors are an important facet o…
MORPH: Design Co-optimization with Reinforcement Learning via a Differentiable Hardware Model Proxy
Zhanpeng He, Matei Ciocarlie
We introduce MORPH, a method for co-optimization of hardware design parameters and control policies in simulation using reinforcement learning. Like most co-optimization methods, M…
Decision Making for Human-in-the-loop Robotic Agents via Uncertainty-Aware Reinforcement Learning
Siddharth Singi, Zhanpeng He, Alvin Pan +5
In a Human-in-the-Loop paradigm, a robotic agent is able to act mostly autonomously in solving a task, but can request help from an external expert when needed. However, knowing wh…
Dexterous In-hand Manipulation by Guiding Exploration with Simple Sub-skill Controllers
Gagan Khandate, Cameron Mehlman, Xingsheng Wei +1
Recently, reinforcement learning has led to dexterous manipulation skills of increasing complexity. Nonetheless, learning these skills in simulation still exhibits poor sample-effi…
Sampling-based Exploration for Reinforcement Learning of Dexterous Manipulation
Gagan Khandate, Siqi Shang, Eric T. Chang +5
In this paper, we present a novel method for achieving dexterous manipulation of complex objects, while simultaneously securing the object without the use of passive support surfac…