I am a PhD student at the University of Pennsylvania. My research interests are focused around robotics, computer vision, and machine learning. I am a member of the GRASP lab and I am advised by Professor Kostas Daniilidis. I earned my Masters of Robotics in 2019 from the University of Pennsylvania.

Before coming to Penn, I worked at MIT Lincoln Laboratory. I completed my undergraduate degree in CS at University of Massachusetts Amherst.

Selected recent works

Semantic keypoint-based pose estimation from single RGB frames

Karl Schmeckpeper, Philip R. Osteen, Yufu Wang, Georgios Pavlakos, Kenneth Chaney, Wyatt Jordan, Xiaowei Zhou, Konstantinos G. Derpanis, Kostas Daniilidis

Field Robotics 2022

Paper Code

Cross-modal Map Learning for Vision and Language Navigation

Georgios Georgakis, Karl Schmeckpeper, Karan Wanchoo, Soham Dan, Eleni Miltsakaki, Dan Roth, Kostas Daniilidis

IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2022

Website Code Paper

Uncertainty-driven Planner for Exploration and Navigation

Georgios Georgakis, Bernadette Bucher, Anton Arapin, Karl Schmeckpeper, Nikolai Matni, Kostas Daniilidis

IEEE Conference on Robotics and Automation (ICRA), 2022

Paper Code Video

Algorithm Transparency through the Fair Credit Reporting Act (FCRA)

Karl Schmeckpeper*, Sonia Roberts*, Mathieu Ouellet*, Matthew Malencia*, Divya Jain*, Walker Gosrich*, Val Bromberg*

Journal of Science Policy and Governance, Volume 18, Issue 04, 2021

JSPG-NSPN 2021 International Science Policy Memo Competition (2nd Place)


Learning to Map for Active Semantic Goal Navigation

Georgios Georgakis, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Kostas Daniilidis

International Conference on Learning Representations (ICLR), 2022

Paper Code

Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets

Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, Sergey Levine

arXiv Preprint


An Adversarial Objective for Scalable Exploration

Bernadette Bucher*, Karl Schmeckpeper*, Nikolai Matni, Kostas Daniilidis

IROS 2021

Website Paper

Object-centric Video Prediction without Annotation

Karl Schmeckpeper*, Georgios Georgakis*, Kostas Daniilidis

IEEE Conference on Robotics and Automation (ICRA), 2021

Paper Code Video

Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, and Chelsea Finn

CoRL 2020.


Learning Predictive Models from Observation and Interaction

Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine, and Chelsea Finn

ECCV 2020.

Website Paper arXiv Video (1min) Video (8min)

RoboNet: Large-Scale Multi-Robot Learning

Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, and Chelsea Finn

Conference on Robotic Learning 2019.

Website Paper

Visual Planning with Semi-Supervised Stochastic Action Representations

Karl Schmeckpeper, David Han, Kostas Daniilidis, and Oleh Rybkin

Workshop on Generative Modeling and Model-Based Reasoning for Robotics and AI at ICML, 2019.


Autonomous Precision Pouring from Unknown Symmetric Containers

Monroe Kennedy III, Karl Schmeckpeper, Dinesh Thakur, Chenfanfu Jiang, Vijay Kumar and Kostas Daniilidis

IEEE Robotics and Automation Letters 2018.

Paper Video

For a full list of publications, please see my google scholar

Google Scholar


karls (at) seas (dot) upenn (dot) edu