activity
20172021
most citedIterative Closest Labeled Point for Tactile Object Shape Recognition

49 citations · 101 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO20211 cited

When Would You Trust a Robot? A Study on Trust and Theory of Mind in Human-Robot Interactions

Wenxuan Mou, Martina Ruocco, Debora Zanatto +1

Trust is a critical issue in Human Robot Interactions as it is the core of human desire to accept and use a non human agent. Theory of Mind has been defined as the ability to under…

cs.CV202013 cited

LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood

Abhinav Kumar, Tim K. Marks, Wenxuan Mou +6

Modern face alignment methods have become quite accurate at predicting the locations of facial landmarks, but they do not typically estimate the uncertainty of their predicted loca…

cs.RO2018

iCLAP: Shape Recognition by Combining Proprioception and Touch Sensing

Shan Luo, Wenxuan Mou, Kaspar Althoefer +1

For humans, both the proprioception and touch sensing are highly utilized when performing haptic perception. However, most approaches in robotics use only either proprioceptive dat…

cs.RO201738 cited

Localizing the Object Contact through Matching Tactile Features with Visual Map

Shan Luo, Wenxuan Mou, Kaspar Althoefer +1

This paper presents a novel framework for integration of vision and tactile sensing by localizing tactile readings in a visual object map. Intuitively, there are some correspondenc…

cs.RO201749 cited

Iterative Closest Labeled Point for Tactile Object Shape Recognition

Shan Luo, Wenxuan Mou, Kaspar Althoefer +1

Tactile data and kinesthetic cues are two important sensing sources in robot object recognition and are complementary to each other. In this paper, we propose a novel algorithm nam…