Kshitij Goel

I am a final-year Ph.D. student in the Robotics Institute at Carnegie Mellon University. My research aims to create teams of robots that can adapt their agency and knowledge with environmental complexity while operating near their sensing, compute, and physical limits. To this end, I design efficient on-device algorithms, spatially-scalable data structures, and tractable probabilistic reasoning methods.

I am currently affiliated with Resilient Intelligent Systems Laboratory.

Journal Articles

Incremental Multimodal Surface Mapping via Self-Organizing Gaussian
Mixture Models — Incremental Multimodal Surface Mapping via Self-Organizing Gaussian Mixture Models
Kshitij Goel and Wennie Tabib
IEEE Robotics and Automation Letters, Vol. 8 Issue 12, Dec. 2023

Probabilistic Point Cloud Modeling via
Self-Organizing Gaussian Mixture Models — Probabilistic Point Cloud Modeling via Self-Organizing Gaussian Mixture Models
Kshitij Goel, Nathan Michael, and Wennie Tabib
IEEE Robotics and Automation Letters, Vol. 8 Issue 5, May 2023

Autonomous Cave Surveying with an Aerial Robot — Autonomous Cave Surveying with an Aerial Robot
Wennie Tabib, Kshitij Goel, John Yao, Curtis Boirum, and Nathan Michael
IEEE Transactions on Robotics, Vol. 38 Issue 2, Apr. 2022
King-Sun Fu Memorial Best Paper Award (Honorable Mention)

Communication-Efficient Planning and Mapping for Multi-Robot Exploration in Large Environments — Communication-Efficient Planning and Mapping for Multi-Robot Exploration in Large Environments
Micah Corah, Cormac O'Meadhra, Kshitij Goel, and Nathan Michael
IEEE Robotics and Automation Letters, Vol. 4 Issue 2, Apr. 2019

Selected Conference Papers

Distance and Collision Probability Estimation from
Gaussian Surface Models — Distance and Collision Probability Estimation from Gaussian Surface Models
Kshitij Goel and Wennie Tabib
IEEE International Conference on Robotics and Automation (ICRA), 2025 (Under Review)

GIRA: Gaussian Mixture Models for Inference and Robot Autonomy — GIRA: Gaussian Mixture Models for Inference and Robot Autonomy
Kshitij Goel and Wennie Tabib
IEEE International Conference on Robotics and Automation (ICRA), 2024

Hierarchical Collision Avoidance for Adaptive-Speed Multirotor Teleoperation — Hierarchical Collision Avoidance for Adaptive-Speed Multirotor Teleoperation
Kshitij Goel, Yves Georgy Daoud, Nathan Michael, and Wennie Tabib
IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2022
Best Paper Award

Rapid and High-Fidelity Subsurface Exploration with Multiple Aerial Robots — Rapid and High-Fidelity Subsurface Exploration with Multiple Aerial Robots
Kshitij Goel, Wennie Tabib, and Nathan Michael
International Symposium on Experimental Robotics (ISER), 2021
National Science Foundation (NSF) Ph.D. Student Travel Award

Fast Exploration Using Multirotors: Analysis, Planning, and Experimentation — Fast Exploration Using Multirotors: Analysis, Planning, and Experimentation
Kshitij Goel, Micah Corah, Curtis Boirum, and Nathan Michael
Field and Service Robotics (FSR), 2021

Real-Time Information-Theoretic Exploration with Gaussian Mixture Model Maps — Real-Time Information-Theoretic Exploration with Gaussian Mixture Model Maps
Wennie Tabib, Kshitij Goel, John Yao, Mosam Dabhi, Curtis Boirum, and Nathan Michael
Robotics: Science and Systems, 2019
Invited for a IEEE Transactions on Robotics (T-RO) Submission

Teaching

Mobile Robot Algorithms Laboratory — 16-362: Mobile Robot Algorithms Laboratory
Instructors: Wennie Tabib and Kshitij Goel
Carnegie Mellon University, Fall 2023
Alan J. Perlis SCS Graduate Student Teaching Award, 2024

Acknowledgements

My research is supported in part by Uber Carnegie Mellon Presidential Fellowship, US Department of Energy (DOE), National Aeronautics and Space Administration (NASA), U.S. Army Research Ofﬁce, U.S. Army Futures Command, and industry. This website template is borrowed from here. My CV template is borrowed from here.