6 papers
Open-World Object Motion Anticipation via Meta-Learned Semantic Adaptation
Mason Peterson, Gage MacLin, Camilla Tabasso +4
Anticipating the motion of nearby objects is critical for safe and efficient robot navigation. Without a proper understanding of what may move, a robot may plan overly conservative…
Factorized Tactile Representation and Control for Sim-to-Real Manipulation
Siqi Shang, Bianca Aumann, Tye Brady +2
Tactile sim-to-real learning must bridge simulated contact and device-specific sensor responses while preserving information needed for control. We propose a factorized tactile rep…
TACTFUL: Tactile-Driven Exploration For Object Localization and Identification in Confined Environments
Shivani Kamtikar, Chung Hee Kim, Camilla Tabasso +3
Humans effortlessly locate and identify objects by touch alone, even without vision. In contrast, robotic systems rely heavily on vision and struggle with autonomous tactile explor…
Training-Free Object-Agnostic Jam Detection in Fulfillment Centers
Ruiliang Liu, Tina Dongxu Li, Joshua Migdal +3
In fulfillment centers, diverse objects move continuously from inbound to outbound operations and can become jammed due to excessive conveyor friction, incorrect orientation, or me…
Enhancing Computer Vision Model Generalization in Warehouse Facilities: A Case Study on Anomaly Detection in Vertical Material Handling Systems
Ruiliang Liu, Tina Dongxu Li, Joshua Migdal +2
Deploying computer vision models in Warehouse Facilities traditionally requires extensive resources for camera mounting, image collection, annotation, training, and deployment - a…
Grasp, Slide, Roll: Comparative Analysis of Contact Modes for Tactile-Based Shape Reconstruction
Chung Hee Kim, Shivani Kamtikar, Tye Brady +2
Tactile sensing allows robots to gather detailed geometric information about objects through physical interaction, complementing vision-based approaches. However, efficiently acqui…