Carson Kohlbrenner
I'm a Master's student with the Human Interaction & Robotics Group at the University of Colorado Boulder advised by Alessandro Roncone. My research interests lie in whole-body perception and learning for collaborative generalized robotics with a focus on tactile sensing and foundation models.
I completed my undergraduate degree in Aerospace Engineering with a minor in Computer Science at the University of Colorado Boulder. It was there where I first discovered my passion for robotics by developing autonomous drone and rocket motion planners.
When I'm not immersed in the world of robotics and research, you can find me enjoying a round of golf, producing music, or enjoying the outdoors. I am always interested in new opportunities and collaborations!
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GenTact Toolbox: A Computational Design Pipeline to Procedurally Generate Context-Driven 3D Printed Whole-Body Tactile Skins
Carson Kohlbrenner,
Caleb Escobedo,
S. Sandra Bae,
Alexander Dickhans,
Alessandro Roncone,
ICRA, 2025
project page
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code
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arXiv
A system for creating whole-body tactile skins that can be procedurally generated to adapt to arbitrary environments. All sensors are 3D printable and simulatable in Isaac Sim.
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A Machine Learning Approach to Contact Localization in Variable Density Three-Dimensional Tactile Artificial Skin
Carson Kohlbrenner,
Mitchell Murray,
Yutong Zhang,
Caleb Escobedo,
Thomas Dunnington,
Nolan Stevenson,
Nikolaus Correll,
Alessandro Roncone
NeurIPS - Workshop on Touch Processing, 2024
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arXiv
Near fingertip level accuracy for contact localization was achieved without locating internal sensors in a variable density tactile skin.
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A Sensor Position Localization Method for Flexible, Non-uniform Capacitive Tactile Sensor Arrays
Carson Kohlbrenner,
Caleb Escobedo,
Nataliya Nechyporenko,
Alessandro Roncone
arXiv Preprint, 2024
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arXiv
An explicit algorithm for localizing the position of capacitive sensors in a flexible, non-uniform sensor array.
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Training CLIP to Recognize Objects with Tactile Sensors
Carson Kohlbrenner,
Nikolaus Correll
Transformer Based Robotic AI, 2024
article
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code
A step-by-step guide to training vision transformers to recognize objects with tactile sensors using contrastive learning.
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Self-Landing Rocket using Deep Reinforcement Learning
Carson Kohlbrenner,
Owen Craig,
Thomas Dunnington,
Decision Making Under Uncertainty Final Project, 2024
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code
Deep Q-network, behavior cloning, and heuristic PID control methods for safely landing a rocket on a platform are implemented and compared.
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Autonomous Localization for GPS-denied Aerial Tracking and Reconnaissance (ALLIGATR)
Carson Kohlbrenner,
Thomas Dunnington,
Nolan Stevenson,
Nyah Baltazar,
Andrew Kabos,
Marcus Quintanilla,
Yarden Kelmann,
Blair Schulze,
Nicholas Grant,
Zane Vandivere,
Lucia Witikko,
Brendan Bradley,
Senior Capstone Project, 2024
final report
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code
An autonomous drone equipped with two cameras for tracking moving targets with computer vision. Targets were successfully localized within 2 meters RMS.
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Linear Temporal Logic Planning for Quadcopter Reconnaissance in Densely Populated Environments
Carson Kohlbrenner,
Nolan Stevenson,
Motion Planning Final Project, 2023
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code
Satellite images of densely populated forests are used to plan waypoints for a quadcopter to fly through while avoiding obstacles. Waypoints allow RRT to visit targets in a set order and avoid obstacles.
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