Maintaining object grasp stability represents a pivotal challenge within the domain of robotic manipulation and upper-limb prosthetics. Perturbations originating from external sources frequently disrupt the stability of grasps, resulting in slippage occurrences. Also, if the grasping forces are not optimal while controlling the slip, it may result in the deformation of the objects. This study investigates the robustification of a reinforcement learning (RL) policy for implementing intelligent bionic reflex control, i.e., slip and deformation prevention of the grasped objects. RL-derived policies are vulnerable to failures in environments characterized by dynamic variability. To mitigate this vulnerability, we propose a methodology involving the incorporation of an adaptive sliding mode controller into a pre-trained RL policy. By exploiting the inherent invariance property of the sliding mode algorithm in the presence of uncertainties, our approach strengthens the robustness of the RL policies against diverse and dynamic variations. Numerical simulations substantiate the efficacy of our approach in robustifying RL policies trained within simulated environments.

The demand for flexible grasping of various objects by robotic hands in the industry is rapidly growing. To address this, we propose a novel variable stiffness gripper (VSG). The VSG design is based on a parallel-guided beam structure inserted by a slider from one end, allowing stiffness variation by changing the length of the parallel beams participating in the system. This design enables continuous adjustment between high compliance and high stiffness of the gripper fingers, providing robustness through its mechanical structure. The linear analytical model of the deflection and stiffness of the parallel beam is derived, which is suitable for small and medium deflections. The contribution of each parameter of the parallel beam to the stiffness is analyzed and discussed. Also, a prototype of the VSG is developed, achieving a stiffness ratio of 70.9, which is highly competitive. Moreover, a vision-based force sensing method utilizing ArUco markers is proposed as a replacement for traditional force sensors. By this method, the VSG is capable of closed-loop control during the grasping process, ensuring efficiency and safety under a well-defined grasping strategy framework. Experimental tests are conducted to emphasize the importance and safety of stiffness variation. In addition, it shows the high performance of the VSG in adaptive grasping for asymmetric scenarios and its ability to flexible grasping for objects with various hardness and fragility. These findings provide new insights for future developments in the field of variable stiffness grippers.

In order to complete many complex operations and attain more general-purpose utility, robotic grasp is a necessary skill to master. As the most common essential action of robots in factory and daily life environments, robotic autonomous grasping has a wide range of application prospects and has received much attention from researchers in the past decade. However, the accurate grasp of arbitrary objects in unstructured environments is still a research challenge that has not yet been completely overcome. A complete robotic grasp system usually involves three aspects: grasp detection, grasp planning, and control subsystem. As the first step, identifying the location of the object and generating the grasp pose is the premise of successful grasp, which is conducive to planning the subsequent grasp path and the realization of the entire grasp action. Therefore, this paper conducts a literature review focusing on grasp detection technology and concludes two significant aspects: the analytic and data-driven methods. According to the previous grasp experience of the target object, this paper divides the data-driven methods into the grasp of known and unknown objects. Then it describes in detail the typical grasp detection methods and related characteristics of each classification in the grasp of unknown objects. Finally, current research status and potential research directions in this field are discussed to provide some reference for related research.

In this paper, the realization of any specified planar Cartesian compliance for an object grasped by a compliant hand is addressed. The hands considered have 2 or more fingers for which each has 3 modulated elastic joints and predetermined link lengths. Geometric construction-based compliance synthesis procedures are developed. Using these procedures, a large set of compliant behaviors can be realized by a single hand simply by adjusting the configuration of each finger and by adjusting the joint stiffness (using variable stiffness actuation) of each finger joint.

This paper presents a study on the effect of design parameters of an underactuated hand on its grasp performance. Three kinds of grasp performance characteristics are considered: grasp range, grasp strength, and immobilizing grasp range. Grasp strength is defined as the stiffness of the grasp. Immobilizing grasps are those in which the object cannot be moved for a force up to a certain threshold. In general, underactuated hands cannot produce immobilizing grasps. However, we show that immobilizing grasps can be created by including joint limits in the hand design. We consider the effect of two design parameters on the grasp performance: torque ratio and finger-base distance. Results show that an optimal finger-base distance and torque ratio exists that maximizes the grasp range and grasp strength. Also, the immobilizing grasp range is increased by decreasing the finger-base distance and increasing the torque ratio and joint limits.

Determining an appropriate grasp configuration for multi-finger grasping is difficult due to the complexity of robotic hands. The multi-finger grasp planning should consider not only geometry constraints of objects but also kinematics and dynamics of robotic hand. In this paper, a precision grasp-planning framework is presented for multi-finger hand to grasp unknown objects. First, the manipulation capabilities of the robotic hand are analyzed. The analysis results are further used as bases for the precision grasp planning. Second, the superquadric (SQ) fitting method is used for approximating unknown object models. Finally, a local–global optimization method is implemented to find appropriate grasp configurations for dexterous hand. The presented planning framework is validated in simulation experiments. Simulation results demonstrated that the presented grasp-planning framework enables the multi-finger hand to grasp unknown objects effectively.

A new theory in contact pressure distribution and friction limit surfaces for modeling of hemicylindrical soft fingertips is introduced, to define the relationship between friction force and the moment with respect to the normal axis of contact. A general pressure-distribution function is proposed to capture material properties and contact geometry with various pressure profiles, and the coefficient of pressure distribution over the rectangular contact area is found between π and π/2. Combining the results of the contact mechanics model with the contact pressure distribution, the normalized friction limit surface can be derived for anthropomorphic soft fingers. The numerical friction limit surface of hemicylindrical soft-finger contact can be approximated by an ellipse, with the major and minor axes as the maximum friction force and the maximum moment with respect to the normal axis of contact, respectively. The results show that the friction limit surfaces are improved (13%–17%), if hemicylindrical fingertips are used rather than hemispherical fingertips at the same radius of fingertip, shape factor of the pressure profile, and applied load. Furthermore, the results of the contact mechanics model and the pressure distribution for soft fingers facilitate the construction of numerical friction limit surfaces, enabling to analyze and simulate the contact behaviors of grasping and manipulation in humanoid robots, prosthetic hands, and robotic hands.

In the human body there are many joints whose functions are very similar to revolute joints. To avoid the complexity of these joints, they are usually substituted by revolute joints in many humanoid robots. Revolute joints have purely rotational motion along their fixed axis, while real joints in the human body have Instantaneous Rotational Axis (IRA) due to their configuration. Substitution of this kind of human joints with revolute (hinge) joints in robots changes the kinematics of joints. Knowing the exact characteristics of the moving axis of rotation in human joints is a prerequisite for the kinematic study of a joint. Here the main geometrical difference between these kinds of joints in humans and their simplified (hinge-like) models in robots is described. Then, as a case study, the mechanism of the three joints of the index finger are compared with their hinge-like model using a multi-body code to understand when revolute joints can be substituted for anthropometric joints in hand exoskeletons and robotic hands. Furthermore, the position of IRA and its distance from the center of the condyle of the joint are presented. The concept and the results can be extended for other fingers and all similar joints, and can be used in humanoid robots, hand exoskeletons and robotic hands.

In this paper, a kinematic model of a dual-arm/hand robotic system is derived, which allows the computation of the object position and orientation from the joint variables of each arm and each finger as well as from a suitable set of contact variables. On the basis of this model, a motion planner is designed, where the kinematic redundancy of the system is exploited to satisfy some secondary tasks aimed at ensuring grasp stability and manipulation dexterity without violating physical constraints. To this purpose, a prioritized task sequencing with smooth transitions between tasks is adopted. Afterwards, a controller is designed so as to execute the motion references provided by the planner and, at the same time, achieve a desired contact force exerted by each finger on the grasped object. To this end, a parallel position/force control is considered. A simulation case study has been developed by using the dynamic simulator GRASPIT!, which has been suitably adapted and redistributed.

Human fingers possess mechanical characteristics, which enable them to manipulate objects. In robotics, the study of soft fingertip materials for manipulation has been going on for a while; however, almost all previous researches have been carried on hemispherical shapes whereas this study concentrates on the use of hemicylindrical shapes. These shapes were found to be more resistant to elastic deformations for the same materials. The purpose of this work is to generate a modified nonlinear contact-mechanics theory for modeling soft fingertips, which is proposed as a power-law equation. The contact area of a hemicylindrical soft fingertip is proportional to the normal force raised to the power of γcy, which ranges from 0 to 1/2. Subsuming the Timoshenko and Goodier (S. P. Timoshenko and J. N. Goodier, Theory of Elasticity, 3rd ed. (McGraw-Hill, New York, 1970) pp. 414–420) linear contact theory for cylinders confirms the proposed power equation. We applied a weighted least-squares curve fitting to analyze the experimental data for different types of silicone (RTV 23, RTV 1701, and RTV 240). Our experimental results supported the proposed theoretical prediction. Results for human fingers and hemispherical soft fingers were also compared.

This paper proposes a novel dynamic stable grasping method of an arbitrary polyhedral object for a hand-arm system with hemispherical fingertips. This method makes it possible to satisfy the force/torque equilibrium condition for the immobilization of the object without knowledge of the object. Two control signals are proposed which generate grasping forces normal and tangential to an object surface in a final state. The dynamics of the overall system is modeled and analyzed theoretically. We demonstrate the stable grasping of an arbitrary polyhedral object using the proposed controller through numerical simulations and experiments using a newly developed mechanical hand-arm system.

When computer vision technique is used in robotics, robotic hand–eye calibration is a very important research task. Many algorithms have been proposed for hand–eye calibration. Based on these algorithms, we introduce a new hand–eye calibration algorithm in this paper, which employs the screw motion theory to establish a hand–eye matrix equation by using quaternion and gets a simultaneous result for rotation and translation by solving linear equations. The algorithm proposed in this paper has high accuracy and stable computational efficiency and can be understood easily. Both simulations and real experiments show the superiority of our algorithm over the comparative algorithms.

Three-dimensional (3D) enveloping grasps for dexterous robotic hands possess several advantages over other types of grasps. This paper describes a new method for kinematic 3D enveloping grasp planning. A new idea for grading the 3D grasp search domain for a given object is proposed. The grading method analyzes the curvature pattern and effective diameter of the object, and grades object regions according to their suitability for grasping. A new approach is also proposed for modeling the fingers of the dexterous hand. The grasp planning method is demonstrated for a three-fingered, six degrees-of-freedom, dexterous hand and several 3D objects containing both convex and concave surface patches. Human-like high-quality grasps are generated in less than 20 s per object.

The overall design of Ca.U.M.Ha. (Cassino-Underactuated-Multifinger-Hand) for harvesting horticulture products is presented. Ca.U.M.Ha. shows an anthropomorphic design incorporating four underactuated finger mechanisms and a simplified contrasting thumb, which are all joined to a rigid palm. The pneumatic cylinders of the articulated fingers are operated in parallel in order to give an additional auto-adaptability on the object to grasp. An application of Ca.U.M.Ha. for grasping different shapes of apples is presented.