Optimization of grasping forces with finger deformability and joint parameter variation constraints

This paper deals with optimization of grasping with multi-fingered robot hands, under general constraints such as finger deformability, sliding conditions and object positioning tolerances. A general formalism describing hyperstatic grasping is presented. An optimization criterion based on the minimization of securing forces and torques is introduced. Results concerning numerical simulation of grasping with a three-fingered gripper are presented. >

This paper presents a tele-control system constructed from a multi-fingered robot hand and operator. The angle of the robot hand is controlled by the angle of the operator’s finger, and the operator feels the environmental force, as detected by the robot hand, constituting so-called bilateral master/slave control.

To achieve a successful grasp, gripper attributes such as its geometry and kinematics play a role as important as the object geometry. The majority of previous work has focused on developing grasp methods that generalize over novel object geometry but are specific to a certain robot hand. We propose UniGrasp, an efficient data-driven grasp synthesis method that considers both the object geometry and gripper attributes as inputs. UniGrasp is based on a novel deep neural network architecture that selects sets of contact points from the input point cloud of the object. The proposed model is trained on a large dataset to produce contact points that are in force closure and reachable by the robot hand. By using contact points as output, we can transfer between a diverse set of multifingered robotic hands. Our model produces over 90% valid contact points in Top10 predictions in simulation and more than 90% successful grasps in real world experiments for various known two-fingered and three-fingered grippers. Our model also achieves 93%, 83% and 90% successful grasps in real world experiments for an unseen two-fingered gripper and two unseen multi-fingered anthropomorphic robotic hands.

Optimization of grasping forces in handling of brittle objects

This paper presents a tele-control system constructed from a multi-fingered robot hand and operator. The angle of the robot hand is controlled by the angle of the operator's finger, and the operator feels the environmental force, as detected by the robot hand, constituting so-called bilateral master/slave control. In the experiments, the operator grasped the object in spite of Round Trip Time (RTT) as Osec, 0.56sec, using a multi-fingered humanoid robot hand by master/slave control feeling fingertip force. However, with increases in the RTT, the operation became more difficult. We also analyzed the stability of the master site and the slave site by frequency characteristics. The results showed that this system was unstable. However, grasping by tele-control with a communication delay was demonstrated.

A multi-finger robotic hand with an iris mechanism that we previously developed was driven by a single actuator and could grasp an object by wrapping fingers completely around its circumference at multiple points. However, the blades used to grasp objects were within the robotic hand mechanism, so it could only grasp objects small enough to fit within the hollow disk comprising the outer surface of the device body. Furthermore, the hand could not grasp objects smaller than the thickness of the hollow disk. The multi-fingered robotic hand proposed in this study has a new mechanism in which the blades of the iris are placed outside of the hand mechanism, and fingers shaped as equilateral triangular prisms extend perpendicular to the disk of the robotic hand body and are attached to the blade tip. Placing the blade outside the mechanism and adjusting the gear ratios within allows adjustments to the gripping torque and speed. The vertically extended fingers can thus grasp small objects and objects longer than the blade diameter. In this study, we performed geometric and theoretical analyses of the proposed multi-fingered robotic hand. We then fabricated an actual robotic hand, verified the validity of the analyses.

Multi-finger robotic hands are the main robotic invention for providing assistive movement therapy in hand rehabilitation. In this paper, the concept of task priority is adopted in order to solve the redundancy resolution of a robotic hand. The redundancy parameter has been used to design the inverse kinematic model in order to determine the joint angles when the finger moves to perform the initial subtask of tracing the desired trajectory while considering the secondary subtask of increasing the instantaneous manipulability. Five different human subjects performed the experimentation where the index finger and thumb are allowed to follow the three desired motion trajectories. Markers are placed on the finger joints in order to track the motion and obtain the finger joint angles. Further, the experimental joint angles are compared with those obtained from inverse kinematics. The index finger and thumb behaviour is analysed based on the redundancy resolution scheme. It has been observed that the optimized root-mean-square error remains insignificant of the different subjects performing the motion and the type of motion trajectories adopted for the index finger as well as the thumb. Thereafter, the proposed scheme is applied to a four-finger tendon-actuated robotic hand and it has been observed that the scheme can be applied to solve the redundancies of any robotic hand.

Feasibility of teleoperations with multi-fingered robotic hand for safe extravehicular manipulations

Grasp planning for irregularly shaped objects using multifingered robotic hands is challenging due to the high dimensionality of the search space and a lack of proper modeling methods for object geometry. To address these issues, we propose a grasp planning approach based on Gaussian process implicit surfaces (GPIS). To explore the object geometry and identify feasible contact positions and normals, our method introduces several moving points called attractors along with a dynamical system. The dynamical system constrains and guides the attractors with the partial differentials of the GPIS, which can be conveniently obtained through the linear expression of a GP. The hand motion is also guided by the dynamical system. In addition, an inverse kinematics method, which considers finger joint limits, is developed to simultaneously adjust the palm pose and finger joint angles for a feasible grasp. The performance of our method is demonstrated using various robotic hands and objects, and real robot experiments are conducted to validate the planned grasp's effectiveness in reality. Experimental evaluation demonstrates that the method works for different robotic hands and objects of varying shapes, with a higher likelihood of generating grasps with better quality.

The human hand is an amazing tool, demonstrated by its incredible motor capability and remarkable sense of touch. To enable robots to work in a human-centric environment, it is desirable to endow robotic hands with human-like capabilities for grasping and object manipulation. However, due to its inherent complexity and inevitable model uncertainty, robotic grasping and manipulation remains a challenge. This thesis focuses on grasp adaptation in the face of model and sensing uncertainties: Given an object whose properties are not known with certainty (e.g., shape, weight and external perturbation), and a multifingered robotic hand, we aim at determining where to put the fingers and how the fingers should adaptively interact with the object using tactile sensing, in order to achieve either a stable grasp or a desired dynamic behaviour. A central idea in this thesis is the object-centric dynamics: namely, that we express all control constraints into an object-centric representation. This simplifies computa- tion and makes the control versatile to the type of hands. This is an essential feature that distinguishes our work from other robust grasping work in the literature, where generating a static stable grasp for a given hand is usually the primary goal. In this thesis, grasp adaptation is a dynamic process that flexibly adapts the grasp to fit some purpose from the objectâ s perspective, in the presence of a variety of uncertainties and/or perturbations. When building a grasp adaptation for a given situation, there are two key problems that must be addressed: 1) the problem of choosing an initial grasp that is suitable for future adaptation, and more importantly 2) the problem of design- ing an adaptation strategy that can react adequately to achieve desired behaviour of the grasped object. To address challenge 1 (planning a grasp under shape uncertainty), we propose an approach to parameterizing the uncertainty in object shape using Gaussian Processes (GPs) and incorporate it as a constraint into contact-level grasp planning. To realize the planned contacts using different hands interchangeably, we further develop a prob- abilistic model to predict the feasible hand configurations, including hand pose and finger joints, given the desired contact points only. The model is built using the con- cept of Virtual Frame(VF), and it is independent from the choice of hand frame and object frame. The performance of the proposed approach is validated on two differ- ent robotic hands, an industrial gripper (4 DOF Barrett hand) and a humanoid hand (16 DOF Allegro hand) to manipulate objects of daily use with complex geometry and various texture (a spray bottle, a tea caddy, a jug and a bunny toy). In the second part of this thesis, we propose an approach to the design of adapta- tion strategy to ensure grasp stability in the presence of physical uncertainties of objects(object weight, friction at contacts and external perturbation). Based on an object-level impedance controller, we first design a grasp stability estimator in the object frame using the grasp experience and tactile sensing. Once a grasp is predicted to be unstable during online execution, the grasp adaptation strategy is triggered to improve the grasp stability, by either changing the stiffness at finger level or relocating the position of one fingertip to a better area.

Based on inspiration of human grasping activities, a new idea is developed in this paper that grasping forces in a multifingered robotic hand can be regulated and controlled through its compliance by actively coordinating small joint motions in its fingers. According to this idea, a grasping force control model is formulated by means of a compliance model developed by the authors before, and a novel theory is then developed for grasping force control in a multifingered robot hand. The developed theory is expected to lead to a new force control method which could serve as a promising alternative for the active stiffness method. As an application of the developed theory, a two-fingered planar robotic hand is also analyzed, and the simulation results verify the developed theory.

Original multi-fingered robot hand can use tactile sensors to recognize the contact state and the force of contact, but is not able to recognize the shape of the object grasped just by tactile without vision. This paper proposed a new recognition algorithm of object grasped applied in PESA hand to solve this problem. The equipment consists of angle sensors installed in the finger joints, tactile sensors installed on the fingers and distance sensors installed on the palm, which can estimate the shape and size information of objects grasped through this algorithm by multi-point grasping repeatedly. The results of experiment shows that this algorithm is effective and can help robot hand measure the three-dimensional shape features of the objects grasped when implement its function.

A general approach for controlling the system configuration drift resulting from the presence of nonholonomic constraints and kinematic redundancy in multifingered robot hands is presented. A redundant multifingered robot hand for grasping and manipulating an object using 3-D rolling contacts is considered. The configuration space of a multifingered robot system (i.e., the hand and a grasped object in contact) is described in terms of finger joint variables and contact variables. In the context of motion repeatability, the combined effect of the redundancy in the system generalized variables and the non-integrability of the hand kinematics equations generate undesirable drift of both finger joint variables and finger/object contact locations. A stable method of drive compensation is proposed for controlling a general case of redundant 3-D rolling robot hands that manipulate an object along a given trajectory. >

Multi-finger Robotic hands (MFRH) are desired similar to human hands in order to perform stable grasping and fine manipulation of different objects. Their industrial applications including material handling fulfills the requirement of unique end-effector tool empowering specific reach, payloads, and flexibility. The design and control of dexterous and prosthetic robotic hands is of important concern these days. The performance of these hands depends on their mechanical design, prosthetics etc. The mechanical range of movement must be properly controlled and monitored to get the best performance of the robotic hand. In order to obtain the desired outcome from these robotic hands, various design parameters are discussed. The control issues of the multi-finger hand-arm system in order to interact with the human environment are also discussed. The objective of this paper is to evaluate multi-finger robotic hands capable of grasping a large variety of products. An overview of the relations between the designing features for the robotic hand, its anthropomorphism and dexterity is reported. Also, the best known robotic hands developed so far are reviewed emphasizing on their ergonomics and mechanical features. Based on these parameters, a newly designed four fingered tendon actuated robotic hand is discussed along with its mechanical structure.

This paper proposed a design idea of a novel under-actuated finger mechanism, and designed the finger mechanism. The finger has no actuator in itself, is only driven by the other finger joints and object grasped. The finger is similar to a human finger and can be easily arranged in series to realize a finger with super under-actuation and high integration. It can be mounted in humanoid robot hand to make the hand obtain more DOFs with less actuators, and good grasping function of shape adaptation, decrease the requirement of control system. This paper analyzed the relationship between the grasping force of the finger and its design parameters, proposed the design principle of structure optimization of the finger. Based on the finger, a multi-fingered humanoid robot hand: TH-2 Hand has been designed. TH-2 Hand has many excellent features: high personification, super under-actuation and be very compact, easy to real-time control, small volume, light in weight, strong grasping function, etc.