Adam Kan

I'm a second year undergrad at Carnegie Mellon University majoring in Computer Science and advised by Deepak Pathak and Kenneth Shaw. Previously, I was fortunate to be advised by Tom Funkhouser and Jeannette Bohg, and have worked with Jimmy Wu.

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Research

I'm interested in applying computer vision techniques for use in robots that help humans. My research experience is in building object detection models and visuomotor robot learning policies.

TidyBot: Personalized Robot Assistance with Large Language Models
Jimmy Wu, Rika Antonova, Adam Kan, Marion Lepert, Andy Zeng, Shuran Song, Jeannette Bohg, Szymon Rusinkiewicz, Thomas Funkhouser
Autonomous Robots (AuRo) - Special Issue: Large Language Models in Robotics, 2023
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
Project Page / arXiv

Robots can combine language-based planning and perception with the few-shot summarization capabilities of large language models (LLMs) to infer generalized user preferences that are broadly applicable to future interactions. Methodology is demonstrated in household cleanup tasks.

clean-usnob FlingWAM: Solving Cloth Unfolding Tasks with Angle Value Maps
Adam Kan, Jimmy Wu, Jeannette Bohg
Working Paper
PDF

Utilizing current image segmentation abilities to detect the edges and centroids of cloths for bimanual unfolding tasks in sim. Our method represents grasp points by using angle value maps instead of spatial value maps to take advantage of generalizable physical characteristics of cloth unfolding tasks.


Modified template from here.