10 papers
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…
Human2Any: Human-to-Robot Transfer via Constraint-Aware Compositional Planning
Shuo Cheng, Chuye Zhang, Alfred Cueva +3
Human videos are a scalable source of supervision for robot manipulation, as they are abundant and naturally capture rich object interactions. However, transferring human demonstra…
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…
HumanoidMimicGen: Data Generation for Loco-Manipulation via Whole-Body Planning
Kevin Lin, Ajay Mandlekar, Caelan Reed Garrett +7
Imitation learning is a promising approach for training humanoid robots to both walk and manipulate, but it requires a large number of demonstrations, which are time-intensive and…
Open-World Task and Motion Planning via Vision-Language Model Generated Constraints
Nishanth Kumar, William Shen, Fabio Ramos +4
Foundation models like Vision-Language Models (VLMs) excel at common sense vision and language tasks such as visual question answering. However, they cannot yet directly solve comp…
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…