Publications

Our publications provide insight into some of our leading-edge research.

Filters

Filters

Publication Year

Research Areas

Events

2024

Diffusion-Reward Adversarial Imitation Learning
Chun-Mao Lai, Hsiang-Chun Wang, Ping-Chun Hsieh, Frank Wang, Min-Hung Chen, Shao-Hua Sun
MaskedMimic: Unified Physics-Based Character Control Through Masked Motion Inpainting
Chen Tessler, Kelly Guo, Ofir Nabati, Gal Chechik, Jason Peng
Differentiable GPU-Parallelized Task and Motion Planning
William Shen, Caelan Garrett, Ankit Goyal, Tucker Hermans, Fabio Ramos
SPIRE: Synergistic Planning, Imitation, and Reinforcement Learning for Long-Horizon Manipulation
Zihan Zhou, Animesh Garg, Dieter Fox, Caelan Garrett, Ajay Mandlekar
SkillGen: Automated Demonstration Generation for Efficient Skill Learning and Deployment
Caelan Garrett, Ajay Mandlekar, Bowen Wen, Dieter Fox
NOD-TAMP: Generalizable Long-Horizon Planning with Neural Object Descriptors
Shuo Cheng, Caelan Garrett, Ajay Mandlekar, Danfei Xu
HAMSTER: Hierarchical Action Models for Open-World Robot Manipulation
Yi Li, Yuquan Deng, Jesse Zhang, Joel Jang, Marius Memmel, Caelan Garrett, Fabio Ramos, Dieter Fox, Anqi Li, Abhishek Gupta, Ankit Goyal
Open-World Task and Motion Planning via Vision-Language Model Inferred Constraints
Nishanth Kumar, Fabio Ramos, Dieter Fox, Caelan Garrett
Guiding Long-Horizon Task and Motion Planning with Vision Language Models
Zhutian Yang, Caelan Garrett, Dieter Fox, Tomás Lozano-Pérez, Leslie Pack Kaelbling
Constructability-driven design of frame structures with state-space search methods
Yijiang Huang, Caelan Garrett, Caitlin Mueller
Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning
Ryan Hoque, Ajay Mandlekar, Caelan Garrett, Ken Goldberg, Dieter Fox
DiMSam: Diffusion Models as Samplers for Task and Motion Planning under Partial Observability
Xiaolin Fang, Caelan Garrett, Clemens Eppner, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Dieter Fox
Best Conference Paper Finalist
Best Student Paper Finalist
Learning to Move Like Professional Counter-Strike Players
David Durst, F. Xie, V. Sarukkai, Brennan Shacklett, Iuri Frosio, Chen Tessler, Joohwan Kim, C. Taylor, G. Bernstein, S. Choudhury, P. Hanrahan,, Kayvon Fatahalian