533 citations · 557 across the 3 of their papers we have counts for
6 papers
Learning to Represent Haptic Feedback for Partially-Observable Tasks
Jaeyong Sung, J. Kenneth Salisbury, Ashutosh Saxena
The sense of touch, being the earliest sensory system to develop in a human body [1], plays a critical part of our daily interaction with the environment. In order to successfully…
Robobarista: Learning to Manipulate Novel Objects via Deep Multimodal Embedding
Jaeyong Sung, Seok Hyun Jin, Ian Lenz +1
There is a large variety of objects and appliances in human environments, such as stoves, coffee dispensers, juice extractors, and so on. It is challenging for a roboticist to prog…
Deep Multimodal Embedding: Manipulating Novel Objects with Point-clouds, Language and Trajectories
Jaeyong Sung, Ian Lenz, Ashutosh Saxena
A robot operating in a real-world environment needs to perform reasoning over a variety of sensor modalities such as vision, language and motion trajectories. However, it is extrem…
Robobarista: Object Part based Transfer of Manipulation Trajectories from Crowd-sourcing in 3D Pointclouds
Jaeyong Sung, Seok Hyun Jin, Ashutosh Saxena
There is a large variety of objects and appliances in human environments, such as stoves, coffee dispensers, juice extractors, and so on. It is challenging for a roboticist to prog…
Synthesizing Manipulation Sequences for Under-Specified Tasks using Unrolled Markov Random Fields
Jaeyong Sung, Bart Selman, Ashutosh Saxena
Many tasks in human environments require performing a sequence of navigation and manipulation steps involving objects. In unstructured human environments, the location and configur…
Unstructured Human Activity Detection from RGBD Images
Jaeyong Sung, Colin Ponce, Bart Selman +1
Being able to detect and recognize human activities is essential for several applications, including personal assistive robotics. In this paper, we perform detection and recognitio…