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Yu Sun

Professor

COMPUTER SCIENCE AND ENGINEERING | COLLEGE OF ENGINEERING

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Research Terms & Keywords

Research Terms

Computer Science Artificial Intelligence Computer Vision Robotics

Research Projects

Ends

Title

07-2029

Developing AI-Driven Pain Intensity and Pain Sensitizati Developing AI-Driven Pain Intensity and Pain Sensitizati

National Institutes of Health

06-2026

POSE: Phase II: Collaborative Open-source Manipulation P POSE: Phase II: Collaborative Open-source Manipulation P

University of Massachusetts

06-2023

An AI-based multimodal approach to predict Pain in postn An AI-based multimodal approach to predict Pain in postn

Stereology Resource Center, Inc.

06-2022

RI: Small: Generalizing Learned Manipulation Skills to Unseen Situations By Balancing Uncertainties RI: Small: Generalizing Learned Manipulation Skills to Unseen Situations By Balancing Uncertainties

National Science Foundation

01-2022

A Multimodal Approach for Monitoring Prolonged Acute Pai A Multimodal Approach for Monitoring Prolonged Acute Pai

National Institutes of Health

06-2021

CHS: Small: Collaborative Research: Wearable Fingertip H CHS: Small: Collaborative Research: Wearable Fingertip H

National Science Foundation

12-2020

REU Site on Ubiquitous Sensing REU Site on Ubiquitous Sensing

National Science Foundation

08-2020

Microsoft Research Dissertation Grant -- Searching High Microsoft Research Dissertation Grant -- Searching High

Microsoft Research Cambridge

04-2019

An Automated Pressure Ulcer Monitoring System to Improve An Automated Pressure Ulcer Monitoring System to Improve

Tampa VA Research & Education Foundation

09-2018

Developing Deep Neural Networks to Detect Objects and Th Developing Deep Neural Networks to Detect Objects and Th

EvaTech

02-2018

EAGER: Characterizing Physical Interaction in Instrument EAGER: Characterizing Physical Interaction in Instrument

National Science Foundation

07-2017

RI: Small: Functional Object-Oriented Network for Manipu RI: Small: Functional Object-Oriented Network for Manipu

National Science Foundation

08-2011

CPS: Small: Virtually Transparent Epidermal Imagery CPS: Small: Virtually Transparent Epidermal Imagery

National Science Foundation

Degrees

Ph.D., Computer Science

University of Utah ▪ 2007

Publications

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Professional Presentations

Task-Oriented Grasp Planning Based on Disturbance Distribution; ISRR; ISRR; 2013

Grasp Planning Based on Grasp Strategy Extraction from Demonstration; IEEE/RSJ International Conference on Intelligent Robots and Systems; IEEE; 2014

Functional Analysis of Grasping Motion; IEEE/RSJ International Conference on Intelligent Robots and Systems; IEEE; 2013

Grasp Mapping Using Locality Preserving Projections and KNN Regression; IEEE Intl. Conference on Robotics and Automation; IEEE; 2013

Human-Object-Object-Interaction Affordance; Workshop in Robot Vision (WoRV)/Winter Vision Meeting ; IEEE; 2013

Five Most Important Trends in Robotics Research; Link: Hardware Partners @ Silicon Valley; Makerlink; 2015

Determining the Benefit of Human Input in Human-in-the-Loop Robotic Systems; IEEE ROMAN ; IEEE; 2013

Virtually Transparent Epidermal Imagery; NSF CPS PI Meeting; NSF; 2013

From Knowledge to Action-- Toward Robotic Cooking; ICRA Workshop on Sensor-Based Object Manipulation for Collaborative Assembly; International Conference on Robotics and Automation; 2017

Hand and Mind; Singularity University; 2016

Ideomotor Learning for Robotic Manipulation; Bay Area Robotics Symposium; Stanford University; 2016

Bring AI into Physical World through Robotic Hands; Google; 2016

Renaissance of Robotic Grasping; CCF Global Artificial Intelligence & Robotics Summit; Chinese Computing Foundation; 2016

Tasks in Robotic Grasping and Manipulation Competitions; IROS Workshop on Development of Benchmarking Protocols for Robot Manipulation; IROS; 2017

Other Professional Activities

Co-Chair, Member Services Committee, Member Activities Board Board Member, Electronic Products and Services Board Associate Editor, IEEE Robotics & Automation Magazine Associate Editor, , IEEE International Conference on Robotics and Automation (ICRA) 2014 Editorial Advisory Board of Assembly Automation journal

Technologies

Systems And Methods For Learning And Generating Movement Policies For A Dynamical System

Competitive Advantages: Adaptable learning, Flexibility in realistic situations, Makes real time decisions. System and methods for generating a trajectory of a dynamical system are described herein. An example method includes modelling a policy from demonstration data. The method also includes generating a first set of action particles by sampling from the policy, where each of the action particles in the first set includes a respective system action, predicting a respective outcome of the dynamical system in response to each of the action particles in the first set, and weighting each of the action particles in the first set according to a respective probability of achieving a desired outcome. The method further includes generating a second set of action particles by sampling from the weighted action particles, where each of the action particles in the second set includes a respective system action, and selecting a next system action in the trajectory of the dynamical system from the action particles in the second set.USF inventors have created a trajectory generation approach that learns a broad and stochastic policy from demonstrations. This approach first learns from the human demonstrations of the policies and is able to generate a trajectory with arbitrary length, and treats the change of the constraints naturally. Based on the magnitude of action and the desired future state, the dynamic system decides to keep, reject or execute samples. The approach weighs the action particles drawn from the policy by their respective likelihood of achieving a desired future outcome, and obtains the optimal action using the weighed actions.

Co-Investigator Network

Sudeep Sarkar

Professor and Associate Vice President For Research & Innovation

Yu Sun

Professor

COMPUTER SCIENCE AND ENGINEERING | COLLEGE OF ENGINEERING

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