Chunyao Zhu | Searcharxiv

arXiv2024

Integrating and Evaluating Visuo-tactile Sensing with Haptic Feedback for Teleoperated Robot Manipulation

Telerobotics enables humans to overcome spatial constraints and physically interact with the environment in remote locations. However, the sensory feedback provided by the system to the user is often purely visual, limiting the user's dexterity in manipulation tasks. This work addresses this issue by equipping the robot's end-effector with high-resolution visuotactile GelSight sensors. Using low-cost MANUS-Gloves, we provide the user with haptic feedback about forces acting at the points of contact in the form of vibration signals. We employ two different methods for estimating these forces; one based on estimating the movement of markers on the sensor surface and one deep-learning approach. Additionally, we integrate our system into a virtual-reality teleoperation pipeline in which a human user controls both arms of a Tiago robot while receiving visual and haptic feedback. Lastly, we present a novel setup to evaluate normal force, shear force, and slip. We believe that integrating haptic feedback is a crucial step towards dexterous manipulation in teleoperated robotic systems.

cs.RO↗

arXiv2021

Evaluating Effects of Background Stories on Graph Perception

A graph is an abstract model that represents relations among entities, for example, the interactions between characters in a novel. A background story endows entities and relations with real-world meanings and describes the semantics and context of the abstract model, for example, the actual story that the novel presents. Considering practical experience and prior research, human viewers who are familiar with the background story of a graph and those who do not know the background story may perceive the same graph differently. However, no previous research has adequately addressed this problem. This research paper thus presents an evaluation that investigated the effects of background stories on graph perception. Three hypotheses that focused on the role of visual focus areas, graph structure identification, and mental model formation on graph perception were formulated and guided three controlled experiments that evaluated the hypotheses using real-world graphs with background stories. An analysis of the resulting experimental data, which compared the performance of participants who read and did not read the background stories, obtained a set of instructive findings. First, having knowledge about a graph's background story influences participants' focus areas during interactive graph explorations. Second, such knowledge significantly affects one's ability to identify community structures but not high degree and bridge structures. Third, this knowledge influences graph recognition under blurred visual conditions. These findings can bring new considerations to the design of storytelling visualizations and interactive graph explorations.

cs.HC↗