activity
20142026
most citedCombining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Driving

313 citations · 498 across the 41 of their papers we have counts for

collaborators
Showing 2023Show all

7 papers · 1 filter

cs.LG2023

Marginalized Importance Sampling for Off-Environment Policy Evaluation

Pulkit Katdare, Nan Jiang, Katherine Driggs-Campbell

Reinforcement Learning (RL) methods are typically sample-inefficient, making it challenging to train and deploy RL-policies in real world robots. Even a robust policy trained in si…

cs.RO2023

Learning Task Skills and Goals Simultaneously from Physical Interaction

Haonan Chen, Ye-Ji Mun, Zhe Huang +4

In real-world human-robot systems, it is essential for a robot to comprehend human objectives and respond accordingly while performing an extended series of motor actions. Although…

cs.RO2023★ 1 cited

In Situ Soil Property Estimation for Autonomous Earthmoving Using Physics-Infused Neural Networks

W. Jacob Wagner, Ahmet Soylemezoglu, Dustin Nottage +1

A novel, learning-based method for in situ estimation of soil properties using a physics-infused neural network (PINN) is presented. The network is trained to produce estimates of…

cs.RO2023★ 1 cited

DFields: Dynamic 3D Descriptor Fields for Zero-Shot Generalizable Rearrangement

Yixuan Wang, Mingtong Zhang, Zhuoran Li +5

Scene representation is a crucial design choice in robotic manipulation systems. An ideal representation is expected to be 3D, dynamic, and semantic to meet the demands of diverse…

cs.RO2023★ 1 cited

Neural Informed RRT*: Learning-based Path Planning with Point Cloud State Representations under Admissible Ellipsoidal Constraints

Zhe Huang, Hongyu Chen, John Pohovey +1

Sampling-based planning algorithms like Rapidly-exploring Random Tree (RRT) are versatile in solving path planning problems. RRT* offers asymptotic optimality but requires growing…

cs.RO2023★ 1 cited

Towards Safe Multi-Level Human-Robot Interaction in Industrial Tasks

Zhe Huang, Ye-Ji Mun, Haonan Chen +7

Multiple levels of safety measures are required by multiple interaction modes which collaborative robots need to perform industrial tasks with human co-workers. We develop three in…

cs.RO2023★ 1 cited

User-Friendly Safety Monitoring System for Manufacturing Cobots

Ye-Ji Mun, Zhe Huang, Haonan Chen +4

Collaborative robots are being increasingly utilized in industrial production lines due to their efficiency and accuracy. However, the close proximity between humans and robots can…