Related papers: Active Clothing Material Perception using Tactile …
Tactile perception is crucial for a variety of robot tasks including grasping and in-hand manipulation. New advances in flexible, event-driven, electronic skins may soon endow robots with touch perception capabilities similar to humans.…
Estimation of tactile properties from vision, such as slipperiness or roughness, is important to effectively interact with the environment. These tactile properties help us decide which actions we should choose and how to perform them.…
Manipulation of thin materials is critical for many everyday tasks and remains a significant challenge for robots. While existing research has made strides in tasks like material smoothing and folding, many studies struggle with common…
Tactile perception is an essential ability of intelligent robots in interaction with their surrounding environments. This perception as an intermediate level acts between sensation and action and has to be defined properly to generate…
Vision and touch are two of the important sensing modalities for humans and they offer complementary information for sensing the environment. Robots could also benefit from such multi-modal sensing ability. In this paper, addressing for the…
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…
Hardness is among the most important attributes of an object that humans learn about through touch. However, approaches for robots to estimate hardness are limited, due to the lack of information provided by current tactile sensors. In this…
We present ClothesNet: a large-scale dataset of 3D clothes objects with information-rich annotations. Our dataset consists of around 4400 models covering 11 categories annotated with clothes features, boundary lines, and keypoints.…
Interactive exploration of the unknown physical properties of objects such as stiffness, mass, center of mass, friction coefficient, and shape is crucial for autonomous robotic systems operating continuously in unstructured environments.…
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…
Tactile sensing is essential for robots to perceive and react to the environment. However, it remains a challenge to make large-scale and flexible tactile skins on robots. Industrial machine knitting provides solutions to manufacture…
Material recognition can help inform robots about how to properly interact with and manipulate real-world objects. In this paper, we present a multimodal sensing technique, leveraging near-infrared spectroscopy and close-range high…
We study the problem of learning physical object representations for robot manipulation. Understanding object physics is critical for successful object manipulation, but also challenging because physical object properties can rarely be…
Differentiable simulation has become a powerful tool for system identification. While prior work has focused on identifying robot properties using robot-specific data or object properties using object-specific data, our approach calibrates…
Tactile sensing plays an irreplaceable role in robotic material recognition. It enables robots to distinguish material properties such as their local geometry and textures, especially for materials like textiles. However, most tactile…
Tactile sensing is inherently contact based. To use tactile data, robots need to make contact with the surface of an object. This is inefficient in applications where an agent needs to make a decision between multiple alternatives that…
Humans leverage multiple sensor modalities when interacting with objects and discovering their intrinsic properties. Using the visual modality alone is insufficient for deriving intuition behind object properties (e.g., which of two boxes…
Cutting is a common form of manipulation when working with divisible objects such as food, rope, or clay. Cooking in particular relies heavily on cutting to divide food items into desired shapes. However, cutting food is a challenging task…
General robot manipulation requires the handling of previously unseen objects. Learning a physically accurate model at test time can provide significant benefits in data efficiency, predictability, and reuse between tasks. Tactile sensing…
For humans, the process of grasping an object relies heavily on rich tactile feedback. Most recent robotic grasping work, however, has been based only on visual input, and thus cannot easily benefit from feedback after initiating contact.…