Editorial: ViTac: Integrating Vision and Touch for Multimodal and Cross-Modal Perception.
Shan Luo,Nathan F. Lepora,Uriel Martinez-Hernandez,Joao Bimbo,Huaping Liu +4 more
- Vol. 8, pp 697601-697601
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The article was published on 2021-01-01 and is currently open access. It has received 6 citations till now. The article focuses on the topics: Crossmodal.read more
Citations
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Journal ArticleDOI
DigiTac: A DIGIT-TacTip Hybrid Tactile Sensor for Comparing Low-Cost High-Resolution Robot Touch
TL;DR: The DIGIT-TacTip (DigiTac) as mentioned in this paper is a 3D-printed sensing surface based on the TacTip family of soft biomimetic optical tactile sensors.
Book ChapterDOI
Multimodal perception for dexterous manipulation
TL;DR: In this article , a spatiotemporal attention model was proposed for tactile texture recognition, which takes both spatial features and time dimension into consideration, and paid attention to the salient features in each spatial feature, but also modeled the temporal correlation through the time dimension.
Book ChapterDOI
GelTip tactile sensor for dexterous manipulation in clutter
TL;DR: Geltip as discussed by the authors uses a camera installed at its base to track the deformations of the opaque elastomer that covers its hollow, rigid, and transparent body, which can sense contacts on any location of its surface.
Proceedings ArticleDOI
Visual-Tactile Multimodality for Following Deformable Linear Objects Using Reinforcement Learning
TL;DR: In this paper , a Reinforcement Learning agent using different sensing modalities was used to complete the task of following deformable linear objects, for the first time, and extensive experiments showed that the use of both vision and tactile inputs, together with proprioception, with up to 92% of cases, compared to 77% when only one of the signals is given.
Journal ArticleDOI
Pseudo-Haptic Heaviness Influenced by the Range of the C/D Ratio and the Position of the C/D Ratio Within a Given Range
TL;DR: In this article , the amplitude ratio of object movements to the user's actions, the so-called C/D ratio, is a powerful determinant of pseudo-haptic heaviness.
References
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Journal ArticleDOI
GelSight: High-Resolution Robot Tactile Sensors for Estimating Geometry and Force.
TL;DR: This paper reviews the development of GelSight, with the emphasis in the sensing principle and sensor design, and introduces the design of the sensor’s optical system, the algorithm for shape, force and slip measurement, and the hardware designs and fabrication of different sensor versions.
Journal ArticleDOI
The TacTip Family: Soft Optical Tactile Sensors with 3D-Printed Biomimetic Morphologies.
Benjamin Ward-Cherrier,Nicholas Pestell,Luke Cramphorn,Luke Cramphorn,Benjamin Winstone,Maria Elena Giannaccini,Jonathan Rossiter,Nathan F. Lepora +7 more
TL;DR: A range of soft optical tactile sensors with various morphologies fabricated through dual-material 3D printing, inspired by the same biomimetic design principle, suitable for real-world applications in tactile perception, exploration, and manipulation.
Proceedings ArticleDOI
Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks
Michelle A. Lee,Yuke Zhu,Krishnan Srinivasan,Parth Shah,Silvio Savarese,Li Fei-Fei,Animesh Garg,Jeannette Bohg +7 more
TL;DR: This work uses self-supervision to learn a compact and multimodal representation of sensory inputs, which can then be used to improve the sample efficiency of the policy learning of deep reinforcement learning algorithms.
Proceedings ArticleDOI
Retrographic sensing for the measurement of surface texture and shape
TL;DR: A novel device that can be used as a 2.5D “scanner” for acquiring surface texture and shape using a slab of clear elastomer covered with a reflective skin that has no moving parts, uses inexpensive materials, and can be made into a portable device that is used “in the field” to record surface shape and texture.
Journal ArticleDOI
Robotic tactile perception of object properties: A review
TL;DR: In this article, a survey extensively reviews current trends in robot tactile perception of object properties, including shape, surface material and object pose, and the role of touch sensing in combination with other sensing sources is discussed.