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相关论文: Optical Tactile Sensing for Aerial Multi-Contact I…

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Legged locomotion benefits from embodied sensing, where perception emerges from the physical interaction between body and environment. We present a soft-surfaced, vision-based tactile foot sensor that endows a bipedal robot with a skin-like…

机器人学 · 计算机科学 2026-02-25 Jaeeun Kim , Junhee Lim , Yu She

Tactile sensing has seen a rapid adoption with the advent of vision-based tactile sensors. Vision-based tactile sensors provide high resolution, compact and inexpensive data to perform precise in-hand manipulation and human-robot…

机器人学 · 计算机科学 2021-07-26 Arpit Agarwal , Tim Man , Wenzhen Yuan

This paper explores the process of designing an automatic multi-sensor drone detection system. Besides the common video and audio sensors, the system also includes a thermal infrared camera, which is shown to be a feasible solution to the…

计算机视觉与模式识别 · 计算机科学 2020-10-20 Fredrik Svanstrom , Cristofer Englund , Fernando Alonso-Fernandez

Deep learning combined with high-resolution tactile sensing could lead to highly capable dexterous robots. However, progress is slow because of the specialist equipment and expertise. The DIGIT tactile sensor offers low-cost entry to…

机器人学 · 计算机科学 2022-07-19 Nathan F. Lepora , Yijiong Lin , Ben Money-Coomes , John Lloyd

Tactile sensing in soft robots remains particularly challenging because of the coupling between contact and deformation information which the sensor is subject to during actuation and interaction with the environment. This often results in…

机器人学 · 计算机科学 2023-05-03 Delin Hu , Zhou Chen , Paul Baisamy , Zhe Liu , Francesco Giorgio-Serchi , Yunjie Yang

Robotic disassembly involves contact-rich interactions in which successful manipulation depends not only on geometric alignment but also on force-dependent state transitions. While vision-based policies perform well in structured settings,…

Vision-based learning from demonstrations has achieved remarkable success in enabling robots to perform manipulation tasks and high-level semantic reasoning, yet it remains insufficient for complex, contact-rich manipulation. While there is…

Humans display the remarkable ability to sense the world through tools and other held objects. For example, we are able to pinpoint impact locations on a held rod and tell apart different textures using a rigid probe. In this work, we…

机器人学 · 计算机科学 2021-10-01 Tasbolat Taunyazov , Luar Shui Song , Eugene Lim , Hian Hian See , David Lee , Benjamin C. K. Tee , Harold Soh

Drone-based rapid and accurate environmental edge detection is highly advantageous for tasks such as disaster relief and autonomous navigation. Current methods, using radars or cameras, raise deployment costs and burden lightweight drones…

Mid-air haptics create a new mode of feedback to allow people to feel tactile sensations in the air. Ultrasonic arrays focus acoustic radiation pressure in space, to induce tactile sensation from the resulting skin deflection. In this work,…

机器人学 · 计算机科学 2022-07-05 Noor Alakhawand , William Frier , Nathan F. Lepora

Tactile sensing is a fundamental modality for embodied intelligence, offering unique and direct feedback on contact geometry, material properties, and interaction dynamics that remote sensors cannot replace. However, unimodal tactile…

Tactile sensing is a essential for skilled manipulation and object perception, but existing devices are unable to capture mechanical signals in the full gamut of regimes that are important for human touch sensing, and are unable to emulate…

机器人学 · 计算机科学 2019-08-23 Yitian Shao , Hui Hu , Yon Visell

Tactile sensing is a crucial perception mode for robots and human amputees in need of controlling a prosthetic device. Today robotic and prosthetic systems are still missing the important feature of accurate tactile sensing. This lack is…

机器人学 · 计算机科学 2022-03-30 Xiaying Wang , Fabian Geiger , Vlad Niculescu , Michele Magno , Luca Benini

In the human hand, high-density contact information provided by afferent neurons is essential for many human grasping and manipulation capabilities. In contrast, robotic tactile sensors, including the state-of-the-art SynTouch BioTac, are…

机器人学 · 计算机科学 2021-01-15 Yashraj S. Narang , Balakumar Sundaralingam , Karl Van Wyk , Arsalan Mousavian , Dieter Fox

Tactile sensing represents a crucial technique that can enhance the performance of robotic manipulators in various tasks. This work presents a novel bioinspired neuromorphic vision-based tactile sensor that uses an event-based camera to…

机器人学 · 计算机科学 2024-03-18 Omar Faris , Mohammad I. Awad , Murana A. Awad , Yahya Zweiri , Kinda Khalaf

Traditional methods for achieving high localization accuracy on tactile sensors usually involve a matrix of miniaturized individual sensors distributed on the area of interest. This approach usually comes at a price of increased complexity…

Tactile sensing provides robots with rich feedback during manipulation, enabling a host of perception and controls capabilities. Here, we present a new open-source, vision-based tactile sensor designed to promote reproducibility and…

机器人学 · 计算机科学 2024-10-01 Andrea Sipos , William van den Bogert , Nima Fazeli

Retrieving rich contact information from robotic tactile sensing has been a challenging, yet significant task for the effective perception of object properties that the robot interacts with. This work is dedicated to developing an algorithm…

机器人学 · 计算机科学 2019-06-25 Yazhan Zhang , Zicheng Kan , Yang Yang , Alexander Yu Tse , Michael Yu Wang

Distributed tactile sensing remains difficult to scale over large areas: dense sensor arrays increase wiring, cost, and fragility, while many alternatives provide limited coverage or miss fast interaction dynamics. We present Sound of…

机器人学 · 计算机科学 2026-02-20 Xili Yi , Ying Xing , Zachary Manchester , Nima Fazeli

The biological skin enables animals to sense various stimuli. Extensive efforts have been made recently to develop smart skin-like sensors to extend the capabilities of biological skins; however, simultaneous sensing of several types of…

计算机视觉与模式识别 · 计算机科学 2024-01-17 Sho Shimadera , Kei Kitagawa , Koyo Sagehashi , Tomoaki Niiyama , Satoshi Sunada