Carter Sifferman

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

My work utilizes low-level techniques from computational imaging to improve robot perception. I am 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

Publications

	Towards 3D Vision with Low-Cost Single-Photon Cameras Fangzhou Mu, Carter Sifferman*, Sacha Jungerman, Yiquan Li, Mark Han, Michael Gleicher, Mohit Gupta, Yin Li CVPR* , 2024 project page / bibtex / pdf By modeling the image formation process and using a NeRF-like approach, we reconstruct 3D geometry from measurements of a miniature proximity sensor.
	IKLink: End-Effector Trajectory Tracking with Minimal Reconfigurations Yeping Wang, Carter Sifferman, Michael Gleicher ICRA , 2024 bibtex / pdf A method for tracking end effector trajectories while taking minimal breaks to reconfigure the arm position.
	Unlocking the Performance of Proximity Sensors by Utilizing Transient Histograms Carter Sifferman, Yeping Wang, Mohit Gupta, Michael Gleicher RA-L In Proc. 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 Zoë Moore Carter Sifferman, Shaniah Tullis, Mengxuan Ma, Rachel Proffitt, Marjorie Skubic Bioinformatics and Biomedicine (BIBM), 2019 bibtex / pdf A system for automatic assessment of stroke patient recovery (e.g. range of motion), using an in-home depth camera.