6 papers
Dynamic Execution Horizon Prediction for Chunk-based Robot Policies
Yuchi Zhao, Miroslav Bogdanovic, Arjun Sohal +5
Action chunking has become a standard design in modern robot policies, from diffusion/flow policies to vision-language-action models, where the policy predicts a sequence of action…
MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation
Kourosh Darvish, Arjun Sohal, Abhijoy Mandal +20
Accelerated materials discovery is critical for addressing global challenges. However, developing new laboratory workflows relies heavily on real-world experimental trials, and thi…
AnyPlace: Learning Generalized Object Placement for Robot Manipulation
Yuchi Zhao, Miroslav Bogdanovic, Chengyuan Luo +5
Object placement in robotic tasks is inherently challenging due to the diversity of object geometries and placement configurations. To address this, we propose AnyPlace, a two-stag…
AMPLIFY: Actionless Motion Priors for Robot Learning from Videos
Jeremy A. Collins, Loránd Cheng, Kunal Aneja +3
Action-labeled data for robotics is scarce and expensive, limiting the generalization of learned policies. In contrast, vast amounts of action-free video data are readily available…
Accelerating Discovery in Natural Science Laboratories with AI and Robotics: Perspectives and Challenges from the 2024 IEEE ICRA Workshop, Yokohama, Japan
Andrew I. Cooper, Patrick Courtney, Kourosh Darvish +20
Science laboratory automation enables accelerated discovery in life sciences and materials. However, it requires interdisciplinary collaboration to address challenges such as robus…
CLIMB: Language-Guided Continual Learning for Task Planning with Iterative Model Building
Walker Byrnes, Miroslav Bogdanovic, Avi Balakirsky +2
Intelligent and reliable task planning is a core capability for generalized robotics, requiring a descriptive domain representation that sufficiently models all object and state in…