In this paper, the robot grasping for stacked objects is studied based on object detection and grasping order planning. Firstly, a novel stacked object classification network (SOCN) is proposed to realize stacked object recognition. The network takes...
In this study, adaptive pincer grasping of soft pneumatic grippers (SPGs) is considered, and we propose how the performance of soft pneumatic actuators (SPAs) and the stiffness of grasped objects can be accounted for in modeling and control. The gras...
A robot’s ability to grasp moving objects depends on the availability of real-time sensor data in both the far-field and near-field of the gripper. This research investigates the potential contribution of tactile sensing to a task of grasping a...
As the end execution tool of agricultural robots, the manipulator directly determines whether the grasping task can be successfully completed. The human hand can adapt to various objects and achieve stable grasping, which is the highest goal for mani...
Giving robot hands more powerful functions has always been one of the goals pursued by scholars in this field. In this paper, an electromagnetic switching multiple grasping modes robot hand (ESMGM hand) is proposed, which integrates three typical gra...
As an essential perceptual device, the tactile sensor can efficiently improve robot intelligence by providing contact force perception to develop algorithms based on contact force feedback. However, current tactile grasping technology lacks high-perf...
Vision-based pose detection and grasping complex-shaped and thin objects are challenging tasks. We propose an architecture that integrates the Generative Grasping Convolutional Neural Network (GG-CNN) with depth recognition to identify a suitable gra...
The involvement of Robots and automated machines in different industries has increased drastically in recent years. Part of this revolution is accomplishing tasks previously performed by humans with advanced robots, which would replace the entire hum...
Grasping an unknown object in a pile is no easy task for a robot—it is often difficult to distinguish different objects; objects occlude one another; object proximity limits the number of feasible grasps available; and so forth. In this paper,...
With the advancement of tactile sensors, researchers increasingly integrate tactile perception into robotics, but only for tasks such as object reconstruction, classification, recognition, and grasp state assessment. In this paper, we rethink the rel...
The current underactuated robot hands use a single actuator to drive multiple degrees of freedom, enabling them to perform grasping functions. This paper design a multi-mode compound grasping robot finger driven by linkage, called MCG hand. The MCG h...
In this paper, a back-drivable and miniature rotary series elastic actuator (RSEA) is proposed for robotic adaptive grasping. A compact arc grooves design has been proposed to effectively reduce the dimension of the RSEA system. The elastic elements...
When grasping objects in a cluttered environment, a key challenge is to find appropriate poses to grasp effectively. Accordingly, several grasping algorithms based on artificial neural networks have been developed recently. However, these methods req...
In this study, a comprehensive approach for sensing object stiffness through the pincer grasping of soft pneumatic grippers (SPGs) is presented. This study was inspired by the haptic sensing of human hands that allows us to perceive object properties...
In nature, birds can freely observe and rest on the surface of objects such as tree branches, mainly due to their flexible claws, thus this paper is inspired by bird perching and shows two imitation bird claw perching grasping mechanisms in the shape...
Target-oriented grasping has become increasingly important in household and industrial environments, and deploying such systems on mobile robots is particularly challenging due to limited computational resources. To address these limitations, we pres...
Human muscles can generate force and stiffness during contraction. When in contact with objects, human hands can achieve compliant grasping by adjusting the grasping force and the muscle stiffness based on the object’s characteristics. To reali...
Grasping objects of irregular shapes and various sizes remains a key challenge in the field of robotic grasping. This paper proposes a novel RGB-D data-based grasping pose prediction network, termed Cascaded Feature Fusion Grasping Network (CFFGN), d...
A rigid in-plane matrix of suction cups is widely used in robotic end-effectors to grasp objects with flat surfaces. However, this grasping strategy fails with objects having different geometry e.g., spherical and cylindrical. Articulated rigid gripp...
This study introduces a parallel YOLO–GG deep learning network for collaborative robot target recognition and grasping to enhance the efficiency and precision of visual classification and grasping for collaborative robots. First, the paper outl...
Grasping objects in cluttered environments remains a significant challenge in robotics, particularly when dealing with novel objects that have not been previously encountered. This paper proposes a novel approach to address the problem of robustly le...
Researchers all over the world are aiming to make robots with accurate and stable human-like grasp capabilities, which will expand the application field of robots, and development of a reasonable grasping strategy is the premise of this function. In...
Under water, on land, or in the air, creatures use a variety of grasping methods to hunt, avoid predators, or carry food. Numerous studies have been conducted to construct a bionic surface for grasping tasks. This paper reviews the typical biomimetic...
This article presents a deep reinforcement learning (DRL) approach for adaptive robotic grasping in dynamic environments. We developed UR5GraspingEnv, a PyBullet-based simulation environment integrated with OpenAI Gym, to train a UR5 robotic arm with...
In the last few decades, several approaches have been presented to accomplish tasks with robots or autonomous systems in a glovebox; nevertheless, in nuclear facilities, risky operations are still executed by humans that guarantee a high manipulation...
This paper addresses the effects of electric power quality on robotic operations. A general overview is reported to highlight the main characteristics of electric power quality and it’s effects on a powered system by considering an end-user&rsq...
Robots gradually have the ability to plan grasping actions in unknown scenes by learning the manipulation of typical scenes. The grasping pose estimation method, as a kind of end-to-end method, has rapidly developed in recent years because of its goo...
Nowadays, grippers are extensively employed to interact with dynamic and variable objects. Therefore, enhancing the adaptability of grippers is crucial for improving production efficiency and product quality. To address the trade-off between load cap...
Robots equipped with anchoring mechanisms have attractive applications in asteroid exploration. However, complex application scenarios bring great challenges to the modeling and control of anchoring mechanisms. This paper presents a grasping model an...
We propose a dual-module robotic system to tackle the problem of generating and performing antipodal robotic grasps for unknown objects from the n-channel image of the scene. We present an improved version of the Generative Residual Convolutional Neu...
Accurate grasping state detection is critical to the dexterous operation of robots. Robots must use multiple modalities to perceive external information, similar to humans. The direct fusion method of visual and tactile sensing may not provide effect...
The development of Internet of Things (IoT) technology has enabled intelligent robots to have more sensing and decision-making capabilities, broadening the application areas of robots. Grasping operation is one of the basic tasks of intelligent robot...
Multiple-suction-cup grasping can improve the efficiency of bin picking in cluttered scenes. In this paper, we propose a grasp planner for a vacuum gripper to use multiple suction cups to simultaneously grasp multiple objects or an object with a larg...
This paper proposes a grasping method for prosthetic hands based on object geometry and symmetry axis. The method utilizes computer vision to extract the geometric shape, spatial position, and symmetry axis of target objects and selects appropriate g...
Secure grasping of objects in complex scenes is the foundation of many tasks. It is important for robots to autonomously determine the optimal grasp based on visual information, which requires reasoning about the stacking relationship of objects and...
Learning from demonstration (LfD) is a practical method for transferring skill knowledge from a human demonstrator to a robot. Several studies have shown the effectiveness of LfD in robotic grasping tasks to improve the success rate of grasping and t...
Being able to stably grasp with generalization is one of the distinguished capabilities for building a generic grasping system for robots. In this work, we propose a stable grasping method for four-pin parallel grippers within a reinforcement learnin...
In robotic manipulation, object grasping is a basic yet challenging task. Dexterous grasping necessitates intelligent visual observation of the target objects by emphasizing the importance of spatial equivariance to learn the grasping policy. In this...
Robots allow industrial manufacturers to speed up production and to increase the product’s quality. This paper deals with the grasping of partially known industrial objects in an unstructured environment. The proposed approach consists of two m...
Kiwifruit harvesting with robotics can be troublesome due to the clustering feature. The gripper of the end effector will easily cause unstable fruit grasping, or the bending and separation action will interfere with the neighboring fruit because of...
A prerequisite for efficient prehension is the ability to estimate an object’s distance and size. While most studies demonstrate that binocular viewing is associated with a more efficient grasp programming and execution compared to monocular vi...
Underwater vehicle-manipulator system (UVMS) can be applied to fulfill different complex underwater tasks such as grasping, drilling, sampling, etc. It is widely used in the field of oceanographic research, marine exploration, military, and commercia...
Autonomous vision-based aerial grasping is an essential and challenging task for aerial manipulation missions. In this paper, we propose a vision-based aerial grasping system for a Rotorcraft Unmanned Aerial Vehicle (UAV) to grasp a target object. Th...
Robotic manipulation of objects with diverse shapes, sizes, and properties, especially deformable ones, remains a significant challenge in automation, necessitating human-like dexterity through the integration of perception, learning, and control. Th...
Secure and reliable active debris removal methods are crucial for maintaining the stability of the space environment. Continuum robots, with their hyper-redundant degrees of freedom, offer the ability to capture targets of varying sizes and shapes th...
The robotic arm frequently performs grasping tasks in unstructured environments. However, due to the complex network architecture and constantly changing operational environments, balancing between grasping accuracy and speed poses significant challe...
To meet real-time grasping demands in complex environments, this paper proposes a lightweight yet high-performance robotic grasping model. The model integrates large kernel convolution and residual connections to generate grasping information for unk...
For unstructured environment applications, the ability of self-recognition for grasping operations should be guaranteed for manipulators. For this purpose, a grasping process, including instance segmentation, pose estimation, and pose transformation,...
This paper presents a system that combines computer vision and surface electromyography techniques to perform grasping tasks with a robotic hand. In order to achieve a reliable grasping action, the vision-driven system is used to compute pre-grasping...
For the robotic grasping of randomly stacked objects in a cluttered environment, the active multiple viewpoints method can improve grasping performance by improving the environment perception ability. However, in many scenes, it is redundant to alway...
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