141 citations · 399 across the 34 of their papers we have counts for
6 papers · 1 filter
ReinforceGen: Hybrid Skill Policies with Automated Data Generation and Reinforcement Learning
Zihan Zhou, Animesh Garg, Ajay Mandlekar +1
Long-horizon manipulation has been a long-standing challenge in the robotics community. We propose ReinforceGen, a system that combines task decomposition, data generation, imitati…
ScheduleStream: Temporal Planning with Samplers for GPU-Accelerated Multi-Arm Task and Motion Planning & Scheduling
Caelan Garrett, Fabio Ramos
Bimanual and humanoid robots are appealing because of their human-like ability to leverage multiple arms to efficiently complete tasks. However, controlling multiple arms at once i…
The Reality Gap in Robotics: Challenges, Solutions, and Best Practices
Elie Aljalbout, Jiaxu Xing, Angel Romero +9
Machine learning has facilitated significant advancements across various robotics domains, including navigation, locomotion, and manipulation. Many such achievements have been driv…
Learning to Plan & Schedule with Reinforcement-Learned Bimanual Robot Skills
Weikang Wan, Fabio Ramos, Xuning Yang +1
Long-horizon contact-rich bimanual manipulation presents a significant challenge, requiring complex coordination involving a mixture of parallel execution and sequential collaborat…
Generalizable Domain Adaptation for Sim-and-Real Policy Co-Training
Shuo Cheng, Liqian Ma, Zhenyang Chen +3
Behavior cloning has shown promise for robot manipulation, but real-world demonstrations are costly to acquire at scale. While simulated data offers a scalable alternative, particu…
HAMSTER: Hierarchical Action Models For Open-World Robot Manipulation
Yi Li, Yuquan Deng, Jesse Zhang +9
Large foundation models have shown strong open-world generalization to complex problems in vision and language, but similar levels of generalization have yet to be achieved in robo…