5 papers
ManipulationNet: An Infrastructure for Benchmarking Real-World Robot Manipulation with Physical Skill Challenges and Embodied Multimodal Reasoning
Yiting Chen, Kenneth Kimble, Edward H. Adelson +20
Dexterous manipulation enables robots to purposefully alter the physical world, transforming them from passive observers into active agents in unstructured environments. This capab…
Text to Robotic Assembly of Multi Component Objects using 3D Generative AI and Vision Language Models
Alexander Htet Kyaw, Richa Gupta, Dhruv Shah +8
Advances in 3D generative AI have enabled the creation of physical objects from text prompts, but challenges remain in creating objects involving multiple component types. We prese…
ARCH: Hierarchical Hybrid Learning for Long-Horizon Contact-Rich Robotic Assembly
Jiankai Sun, Aidan Curtis, Yang You +8
Generalizable long-horizon robotic assembly requires reasoning at multiple levels of abstraction. While end-to-end imitation learning (IL) is a promising approach, it typically req…
Fabrica: Dual-Arm Assembly of General Multi-Part Objects via Integrated Planning and Learning
Yunsheng Tian, Joshua Jacob, Yijiang Huang +10
Multi-part assembly poses significant challenges for robots to execute long-horizon, contact-rich manipulation with generalization across complex geometries. We present Fabrica, a…
Flow-based Domain Randomization for Learning and Sequencing Robotic Skills
Aidan Curtis, Eric Li, Michael Noseworthy +5
Domain randomization in reinforcement learning is an established technique for increasing the robustness of control policies trained in simulation. By randomizing environment prope…