20 citations · 23 across the 4 of their papers we have counts for
9 papers
Meta-Reinforcement Learning for Robotic Industrial Insertion Tasks
Gerrit Schoettler, Ashvin Nair, Juan Aparicio Ojea +2
Robotic insertion tasks are characterized by contact and friction mechanics, making them challenging for conventional feedback control methods due to unmodeled physical effects. Re…
Information-Collection in Robotic Process Monitoring: An Active Perception Approach
Martin A. Sehr, Wei Xi Xia, Prithvi Akella +2
Active perception systems maximizing information gain to support both monitoring and decision making have seen considerable application in recent work. In this paper, we propose an…
LFZip: Lossy compression of multivariate floating-point time series data via improved prediction
Shubham Chandak, Kedar Tatwawadi, Chengtao Wen +3
Time series data compression is emerging as an important problem with the growth in IoT devices and sensors. Due to the presence of noise in these datasets, lossy compression can o…
UniGrasp: Learning a Unified Model to Grasp with Multifingered Robotic Hands
Lin Shao, Fabio Ferreira, Mikael Jorda +6
To achieve a successful grasp, gripper attributes such as its geometry and kinematics play a role as important as the object geometry. The majority of previous work has focused on…
Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards
Gerrit Schoettler, Ashvin Nair, Jianlan Luo +4
Connector insertion and many other tasks commonly found in modern manufacturing settings involve complex contact dynamics and friction. Since it is difficult to capture related phy…
Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly
Jianlan Luo, Eugen Solowjow, Chengtao Wen +4
Precise robotic manipulation skills are desirable in many industrial settings, reinforcement learning (RL) methods hold the promise of acquiring these skills autonomously. In this…