Related papers: In-Hand Object-Dynamics Inference using Tactile Fi…

Rapid deployment of new tactile sensors is essential for scalable robotic manipulation, especially in multi-fingered hands equipped with vision-based tactile sensors. However, current methods for inferring contact properties rely heavily on…

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…

Robotic grasping requires safe force interaction to prevent a grasped object from being damaged or slipping out of the hand. In this vein, this paper proposes an integrated framework for grasping with formal safety guarantees based on…

This paper presents a novel design of a soft tactile finger with omni-directional adaptation using multi-channel optical fibers for rigid-soft interactive grasping. Machine learning methods are used to train a model for real-time prediction…

Grasping the same object in different postures is often necessary, especially when handling tools or stacked items. Due to unknown object properties and changes in grasping posture, the required grasping force is uncertain and variable.…

The images captured by vision-based tactile sensors carry information about high-resolution tactile fields, such as the distribution of the contact forces applied to their soft sensing surface. However, extracting the information encoded in…

For in-hand manipulation, estimation of the object pose inside the hand is one of the important functions to manipulate objects to the target pose. Since in-hand manipulation tends to cause occlusions by the hand or the object itself, image…

Robotic tactile sensing provides a method of recognizing objects and their properties where vision fails. Prior work on tactile perception in robotic manipulation has frequently focused on exploratory procedures (EPs). However, the…

Brain-computer interface allows people who have lost their motor skills to control robot limbs based on electroencephalography. Most BCIs are guided only by visual feedback and do not have somatosensory feedback, which is an important…

Tactile sensing is essential to the human perception system, so as to robot. In this paper, we develop a novel optical-based tactile sensor "FingerVision" with effective signal processing algorithms. This sensor is composed of soft skin…

We introduce a unified framework for gentle robotic grasping that synergistically couples real-time friction estimation with adaptive grasp control. We propose a new particle filter-based method for real-time estimation of the friction…

This paper addresses the problem of simultaneously exploring an unknown object to model its shape, using tactile sensors on robotic fingers, while also improving finger placement to optimise grasp stability. In many situations, a robot will…

Tactile sensors are breaking into the field of robotics to provide direct information related to contact surfaces, including contact events, slip events and even texture identification. These events are especially important for robotic hand…

In robots, nonprehensile manipulation operations such as pushing are a useful way of moving large, heavy or unwieldy objects, moving multiple objects at once, or reducing uncertainty in the location or pose of objects. In this study, we…

Vision-based tactile sensors have gained extensive attention in the robotics community. The sensors are highly expected to be capable of extracting contact information i.e. haptic information during in-hand manipulation. This nature of…

This work details the design of a novel two finger robot gripper with multiple Gelsight based optical-tactile sensors covering the inner surface of the hand. The multiple Gelsight sensors can gather the surface topology of the object from…

High resolution tactile sensing has great potential in autonomous mobile robotics, particularly for legged robots. One particular area where it has significant promise is the traversal of challenging, varied terrain. Depending on whether an…

Adaptive control for real-time manipulation requires quick estimation and prediction of object properties. While robot learning in this area primarily focuses on using vision, many tasks cannot rely on vision due to object occlusion. Here,…

Tactile sensors provide information that can be used to learn and execute manipulation tasks. Different tasks, however, might require different levels of sensory information; which in turn likely affect learning rates and performance. This…

One of the most important object properties that humans and robots perceive through touch is hardness. This paper investigates information-theoretic active sampling strategies for sample-efficient hardness classification with vision-based…