相关论文: DenseTact 2.0: Optical Tactile Sensor for Shape an…
Camera-based tactile sensors have shown great promise in enhancing a robot's ability to perform a variety of dexterous manipulation tasks. Advantages of their use can be attributed to the high resolution tactile data and 3D depth map…
Inspired by humans' ability to perceive the surface texture of unfamiliar objects without relying on vision, the sense of touch can play a crucial role in robots exploring the environment, particularly in scenes where vision is difficult to…
Grasping object,whether they are flat, round, or narrow and whether they have regular or irregular shapes,introduces difficulties in determining the ideal grasping posture, even for the most state-of-the-art grippers. In this article, we…
This work presents a new version of the tactile-sensing finger GelSlim 3.0, which integrates the ability to sense high-resolution shape, force, and slip in a compact form factor for use with small parallel jaw grippers in cluttered…
In this paper, a novel tactile sensing mechanism for soft robotic fingers is proposed. Inspired by the proprioception mechanism found in mammals, the proposed approach infers tactile information from a strain sensor attached on the finger's…
Real-time proprioception is a challenging problem for soft robots, which have almost infinite degrees-of-freedom in body deformation. When multiple actuators are used, it becomes more difficult as deformation can also occur on actuators…
Tactile sensing has proven to be an invaluable tool for enhancing robotic perception, particularly in scenarios where visual data is limited or unavailable. However, traditional methods for pose estimation using tactile data often rely on…
Reliable real-time 3D shape sensing is essential for robust control and interpretation of deformable systems during motion. Existing vision-based approaches require line-of-sight and complex instrumentation, limiting operation in occluded…
Accurate shape sensing, only achievable through distributed proprioception, is a key requirement for closed-loop control of soft robots. Low-cost power efficient optoelectronic sensors manufactured from flexible materials represent a…
Optical tactile sensors provide robots with rich force information for robot grasping in unstructured environments. The fast and accurate calibration of three-dimensional contact forces holds significance for new sensors and existing…
Tactile perception is essential for human interaction with the environment and is becoming increasingly crucial in robotics. Tactile sensors like the BioTac mimic human fingertips and provide detailed interaction data. Despite its utility…
Tactile sensing allows robots to gather detailed geometric information about objects through physical interaction, complementing vision-based approaches. However, efficiently acquiring useful tactile data remains challenging due to the…
Soft robotic fingers can improve adaptability in grasping and manipulation, compensating for geometric variation in object or environmental contact, but today lack force capacity and fine dexterity. Integrated tactile sensors can provide…
Tactile sensing is an essential capability for robots that carry out dexterous manipulation tasks. While cameras, Lidars and other remote sensors can assess a scene globally and instantly, tactile sensors can reduce their measurement…
This work describes the development of a high-resolution tactile-sensing finger for robot grasping. This finger, inspired by previous GelSight sensing techniques, features an integration that is slimmer, more robust, and with more…
Contact often occurs without macroscopic surface deformation, such as during interaction with liquids, semi-liquids, or ultra-soft materials. However, most existing tactile sensors rely on deformation to infer contact, making such…
Fine dexterous manipulation requires reactive control based on rich sensing of manipulator-object interactions. Tactile sensing arrays provide rich contact information across the manipulator's surface. However their implementation faces two…
Deep learning and reinforcement learning methods have been shown to enable learning of flexible and complex robot controllers. However, the reliance on large amounts of training data often requires data collection to be carried out in…
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…
Recently simulation methods have been developed for optical tactile sensors to enable the Sim2Real learning, i.e., firstly training models in simulation before deploying them on the real robot. However, some artefacts in the real objects…