相关论文: Tactile-Reactive Roller Grasper

This paper presents the technique of flex-and-flip manipulation. It is suitable for grasping thin, flexible linear objects lying on a flat surface. During the manipulation process, the object is first flexed by a robotic gripper whose…

This study proposes a novel robotic gripper with variable grasping configurations for grasping various objects. The fingers of the developed gripper incorporate multiple different surfaces. The gripper possesses the function of altering the…

Bringing tactile sensation to robotic hands will allow for more effective grasping, along with the wide range of benefits of human-like touch. Here we present a 3D-printed, three-fingered tactile robot hand comprising an OpenHand Model O…

The development of robotic grippers is driven by the need to execute particular manual tasks or meet specific objectives in handling operations. Grippers with specific functions vary from being small, accurate and highly controllable such…

Robotic grasp detection is a fundamental capability for intelligent manipulation in unstructured environments. Previous work mainly employed visual and tactile fusion to achieve stable grasp, while, the whole process depending heavily on…

Rotational displacement about the grasping point is a common grasp failure when an object is grasped at a location away from its center of gravity. Tactile sensors with soft surfaces, such as GelSight sensors, can detect the rotation…

The use of anthropomorphic robotic hands for assisting individuals in situations where human hands may be unavailable or unsuitable has gained significant importance. In this paper, we propose a novel task called human-assisting dexterous…

Measuring grasp stability is an important skill for dexterous robot manipulation tasks, which can be inferred from haptic information with a tactile sensor. Control policies have to detect rotational displacement and slippage from tactile…

This paper proposes a novel approach to recognizing dynamic hand gestures facilitating seamless interaction between humans and robots. Here, each robot manipulator task is assigned a specific gesture. There may be several such tasks, hence,…

Robotic hands offer advanced manipulation capabilities, while their complexity and cost often limit their real-world applications. In contrast, simple parallel grippers, though affordable, are restricted to basic tasks like pick-and-place.…

We propose a novel tri-fingered soft robotic gripper with decoupled stiffness and shape control capability for performing adaptive grasping with minimum system complexity. The proposed soft fingers adaptively conform to object shapes…

Grip control during robotic in-hand manipulation is usually modeled as part of a monolithic task, relying on complex controllers specialized for specific situations. Such approaches do not generalize well and are difficult to apply to novel…

This paper develops closed-loop tactile controllers for dexterous robotic manipulation with a dual-palm robotic system. Tactile dexterity is an approach to dexterous manipulation that plans for robot/object interactions that render…

Robots are expected to grasp a wide range of objects varying in shape, weight or material type. Providing robots with tactile capabilities similar to humans is thus essential for applications involving human-to-robot or robot-to-robot…

Despite significant advancements in robotic manipulation, achieving consistent and stable grasping remains a fundamental challenge, often limiting the successful execution of complex tasks. Our analysis reveals that even state-of-the-art…

The advent of tactile sensors in robotics has sparked many ideas on how robots can leverage direct contact measurements of their environment interactions to improve manipulation tasks. An important line of research in this regard is that of…

Robots are increasingly envisioned as human companions, assisting with everyday tasks that often involve manipulating deformable objects. Although recent advances in robotic hardware and embodied AI have expanded their capabilities, current…

Generalized in-hand manipulation has long been an unsolved challenge of robotics. As a small step towards this grand goal, we demonstrate how to design and learn a simple adaptive controller to achieve in-hand object rotation using only…

Reinforcement Learning (RL) methods have been widely applied for robotic manipulations via sim-to-real transfer, typically with proprioceptive and visual information. However, the incorporation of tactile sensing into RL for contact-rich…

This work presents a next-generation human-robot interface that can infer and realize the user's manipulation intention via sight only. Specifically, we develop a system that integrates near-eye-tracking and robotic manipulation to enable…