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Robotic palpation relies on force sensing, but force signals in soft-tissue environments are variable and cannot reliably reveal subtle subsurface features. We present a compact multimodal sensor that integrates high-resolution vision-based…

High-resolution optical tactile sensors are increasingly used in robotic learning environments due to their ability to capture large amounts of data directly relating to agent-environment interaction. However, there is a high barrier of…

Robotics · Computer Science 2022-07-28 Yijiong Lin , John Lloyd , Alex Church , Nathan F. Lepora

We proposed a new type of tactile sensor that is capable of determining the surface morphology of skin lesions. The sensor consists of a brass cylinder with an axial bore. Three peripheral bobbins were machined in the cylinder around which…

With the development of robot electronic skin technology, various tactile sensors, enhanced by AI, are unlocking a new dimension of perception for robots. In this work, we explore how robots equipped with electronic skin can recognize…

Robotics · Computer Science 2025-06-24 Shuo Jiang , Boce Hu , Linfeng Zhao , Lawson L. S. Wong

Developing artificial tactile sensing capabilities that rival human touch is a long-term goal in robotics and prosthetics. Gradually more elaborate biomimetic tactile sensors are being developed and applied to grasping and manipulation…

Robotics · Computer Science 2020-10-28 Benjamin Ward-Cherrier , Nicholas Pestell , Nathan F. Lepora

Optical tactile sensors are extensively utilized in intelligent robot manipulation due to their ability to acquire high-resolution tactile information at a lower cost. However, achieving adequate reality and versatility in simulating…

Robotics · Computer Science 2024-05-07 Zirong Shen , Yuhao Sun , Shixin Zhang , Zixi Chen , Heyi Sun , Fuchun Sun , Bin Fang

Terrain-aware perception holds the potential to improve the robustness and accuracy of autonomous robot navigation in the wilds, thereby facilitating effective off-road traversals. However, the lack of multi-modal perception across various…

Robotics · Computer Science 2024-03-26 Chen Yao , Yangtao Ge , Guowei Shi , Zirui Wang , Ningbo Yang , Zheng Zhu , Hexiang Wei , Yuntian Zhao , Jing Wu , Zhenzhong Jia

Tactile sensors can provide detailed contact in-formation that can facilitate robots to perform dexterous, in-hand manipulation tasks. One of the primitive but important tasks is surface following that is a key feature for robots while…

Robotics · Computer Science 2019-12-03 Chen Lu , Jing Wang , Shan Luo

In robotic manipulation, tactile sensors are indispensable, especially when dealing with soft objects, objects of varying dimensions, or those out of the robot's direct line of sight. Traditional tactile sensors often grapple with…

Robotics · Computer Science 2024-05-24 Abraham George , Yibo Chen , Atharva Dikshit , Peter Pak , Amir Barati Farimani

Tactile sensing is crucial in robotics and wearable devices for safe perception and interaction with the environment. Optical tactile sensors have emerged as promising solutions, as they are immune to electromagnetic interference and have…

Reusing the tactile knowledge of some previously-explored objects helps us humans to easily recognize the tactual properties of new objects. In this master thesis, we enable arobotic arm equipped with multi-modal artificial skin, like…

Robotics · Computer Science 2018-07-04 Di Feng

Camera-based tactile sensors are emerging as a promising inexpensive solution for tactile-enhanced manipulation tasks. A recently introduced FingerVision sensor was shown capable of generating reliable signals for force estimation, object…

Tactile feedback is critical for understanding the dynamics of both rigid and deformable objects in many manipulation tasks, such as non-prehensile manipulation and dense packing. We introduce an approach that combines visual and tactile…

Robotics · Computer Science 2024-07-02 Bo Ai , Stephen Tian , Haochen Shi , Yixuan Wang , Cheston Tan , Yunzhu Li , Jiajun Wu

Camera-based tactile sensors provide robots with a high-performance tactile sensing approach for environment perception and dexterous manipulation. However, achieving comprehensive environmental perception still requires cooperation with…

Robotics · Computer Science 2025-04-15 Yueshi Dong , Jieji Ren , Zhenle Liu , Zhanxuan Peng , Zihao Yuan , Ningbin Zhang , Guoying Gu

Multi-legged elongate robots hold promise for maneuvering through complex environments. Prior work has demonstrated that reliable locomotion can be achieved using open-loop body undulation and foot placement on rugose terrain. However,…

In this work, we report on the integrated sensorimotor control of the Pisa/IIT SoftHand, an anthropomorphic soft robot hand designed around the principle of adaptive synergies, with the BRL tactile fingertip (TacTip), a soft biomimetic…

Tactile sensing in mobile robots remains under-explored, mainly due to challenges related to sensor integration and the complexities of distributed sensing. In this work, we present a tactile sensing architecture for mobile robots based on…

Tactile sensing is critical for robotic grasping and manipulation of objects under visual occlusion. However, in contrast to simulations of robot arms and cameras, current simulations of tactile sensors have limited accuracy, speed, and…

Robotics · Computer Science 2021-04-01 Yashraj Narang , Balakumar Sundaralingam , Miles Macklin , Arsalan Mousavian , Dieter Fox

Animals in nature combine multiple modalities, such as sight and feel, to perceive terrain and develop an understanding of how to walk on uneven terrain in a stable manner. Similarly, legged robots need to develop their ability to stably…

Robotics · Computer Science 2026-04-17 Kartikeya Singh , Youngjin Kim , Yash Turkar , Karthik Dantu

This article describes a new way of controlling robots using soft tactile sensors: pose-based tactile servo (PBTS) control. The basic idea is to embed a tactile perception model for estimating the sensor pose within a servo control loop…

Robotics · Computer Science 2021-07-05 Nathan F. Lepora , John Lloyd
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