I am a research scientist at The Boston Dynamics AI Institute. My research interests are focused around the intersection of robotics, computer vision, and machine learning. I completed my PhD at the University of Pennsylvania in the GRASP lab, advised by Professor Kostas Daniilidis. I earned my Masters of Robotics from the University of Pennsylvania and a Bachelor's degree in CS at University of Massachusetts Amherst.
Selected recent works
For a more complete list of publications, please see my Google Scholar or my CV.
EFEM: Equivariant Neural Field Expectation Maximization for 3D Object Segmentation Without Scene Supervision
Jiahui Lei, Congyue Deng, Karl Schmeckpeper, Leonidas Guibas, Kostas Daniilidis
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2023
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
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
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
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
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
Robotics Science and Systems (RSS), 2022
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)
An Adversarial Objective for Scalable Exploration
Bernadette Bucher*, Karl Schmeckpeper*, Nikolai Matni, Kostas Daniilidis
IROS 2021
Object-centric Video Prediction without Annotation
Karl Schmeckpeper*, Georgios Georgakis*, Kostas Daniilidis
IEEE Conference on Robotics and Automation (ICRA), 2021
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.
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.
Contact
first_name.last_name@gmail.com