4 papers
AnyTouch 2: General Optical Tactile Representation Learning For Dynamic Tactile Perception
Ruoxuan Feng, Yuxuan Zhou, Siyu Mei +6
Real-world contact-rich manipulation demands robots to perceive temporal tactile feedback, capture subtle surface deformations, and reason about object properties as well as force…
Phoenix: A Motion-based Self-Reflection Framework for Fine-grained Robotic Action Correction
Wenke Xia, Ruoxuan Feng, Dong Wang +1
Building a generalizable self-correction system is crucial for robots to recover from failures. Despite advancements in Multimodal Large Language Models (MLLMs) that empower robots…
AnyTouch: Learning Unified Static-Dynamic Representation across Multiple Visuo-tactile Sensors
Ruoxuan Feng, Jiangyu Hu, Wenke Xia +5
Visuo-tactile sensors aim to emulate human tactile perception, enabling robots to precisely understand and manipulate objects. Over time, numerous meticulously designed visuo-tacti…
Play to the Score: Stage-Guided Dynamic Multi-Sensory Fusion for Robotic Manipulation
Ruoxuan Feng, Di Hu, Wenke Ma +1
Humans possess a remarkable talent for flexibly alternating to different senses when interacting with the environment. Picture a chef skillfully gauging the timing of ingredient ad…