Carter Sifferman

I am a Computer Science PhD student at University of Wisconsin - Madison, advised by Michael Gleicher and Mohit Gupta.

My work primarily focuses on utilizing low-level techniques from computational imaging to improve robot perception. I am currently most interested in time-of-flight proximity sensors for up-close and distributed robot sensing.

Representative work is highlighted

Email  /  CV  /  X (Twitter)  /  Google Scholar  /  Github

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Publications

Unlocking the Performance of Proximity Sensors by Utilizing Transient Histograms
Carter Sifferman, Yeping Wang, Mohit Gupta, Michael Gleicher,
RA-L To Appear: ICRA , 2024
project page / video / bibtex / code / pdf

Directly utilizing low-level information generated by optical time-of-flight sensors allows recovery of planar geometry and albedo from a single sensor measurement

Exploiting Task Tolerances in Mimicry-based Telemanipulation
Yeping Wang, Carter Sifferman, Michael Gleicher,
IROS , 2023
bibtex / pdf

Allowing a robot to move freely in non task-relevant degrees of freedom improves the telemanipulation experience

Geometric Calibration of Single Pixel Distance Sensors
Carter Sifferman, Dev Mehrotra, Mohit Gupta, Michael Gleicher,
RA-L in Proc. IROS , 2022
project page / video / bibtex / code / pdf

A depth sensor attached to a robot arm can be extrinsically calibrated relative to that robot arm using only an unknown planar surface

Depth sensor-based in-home daily activity recognition and assessment system for stroke rehabilitation
Zoƫ Moore Carter Sifferman, Shaniah Tullis, Mengxuan Ma, Rachel Proffitt, Marjorie Skubic,
Bioinformatics and Biomedicine (BIBM), 2019
bibtex / pdf

We create a system for automatic assessment of stroke patient recovery (e.g. range of motion), using an in-home depth camera

Other Work

A Review of Scene Representations for Robot Manipulators
Carter Sifferman
bibtex / pdf

Increasingly, robots build an internal representation of the world around them from sensor readings. This is a review of such representations for robot manipulators.

Completed as part of my PhD Qualifying Exam

website template from Jon Barron