Search results

Passively compliant underactuated mechanisms are one way to obtain the gripper which could accommodate to any irregular and sensitive grasping object. The purpose of the underactuation is to use less active inputs than the number of degrees of freedom of the gripper mechanism to drive the open and close motion of the gripper. Another purpose of underaction is to reduce the number of control variables.

The underactuation can morph shapes of the gripper to accommodate different objects. As a result, the underactuated grippers require less complex control algorithms. The fully compliant mechanism has multiple degrees of freedom and can be considered as an underactuated mechanism.

This paper presents a new design of the adaptive underactuated compliant gripper with distributed compliance. The optimal topology of the gripper structure was obtained by optimality criteria method using mathematical programming technique. Afterwards, the obtained model was improved by iterative finite element optimization procedure. The gripper was constructed entirely of silicon rubber.

The main points of this paper are the explanation of the development and production of the new compliant gripper structure.

The paper aims to discuss a new design methodology for multi-fingered robotic grippers.

Optimization of the compliant mechanism with underactuation.

A new robotic gripper principle without active control.

Design of multi-fingered robotic gripper as a monolithic structure without joints.

The subject of the paper is the mechatronic design of a novel robotic hand, cassino-underactuated-multifinger-hand (Ca.U.M.Ha.), along with its prototype and the experimental analysis of its grasping of soft and rigid objects with different shapes, sizes and materials. The paper aims to discuss these issues.

Ca.U.M.Ha. is designed with four identical underactuated fingers and an opposing thumb, all joined to a rigid palm and actuated by means of double-acting pneumatic cylinders. In particular, each underactuated finger with three phalanxes and one actuator is able to grasp cylindrical objects with different shapes and sizes, while the common electropneumatic operation of the four underactuated fingers gives an additional auto-adaptability to grasp objects with irregular shapes. Moreover, the actuating force control is allowed by a closed-loop pressure control within the pushing chambers of the pneumatic cylinders of the four underactuated fingers, because of a pair of two-way/two-position pulse-width-modulation (PWM) modulated pneumatic digital valves, which can also be operated under ON/OFF modes.

The grasping of soft and rigid objects with different shapes, sizes and materials is a very difficult task that requires a complex mechatronic design, as proposed and developed worldwide, while Ca.U.M.Ha. offers these performances through only a single ON/OFF or analogue signal.

Ca.U.M.Ha. could find several practical applications in industrial environments since it is characterized by a robust and low-cost mechatronic design, flexibility and easy control, which are based on the use of easy-running components.

Ca.U.M.Ha. shows a novel mechatronic design that is based on a robust mechanical design and an easy operation and control with high dexterity and reliability to perform a safe grasp of objects with different shapes, sizes and materials.

A distinctive feature of tilt-rotor UAVs is that they can be fully actuated, whereas in fixed-angle rotor UAVs (e.g. common-type quadrotors, octorotors, etc.), the associated dynamic model is characterized by underactuation. Because of the existence of more control inputs, in tilt-rotor UAVs, there is more flexibility in the solution of the associated nonlinear control problem. On the other side, the dynamic model of the tilt-rotor UAVs remains nonlinear and multivariable and this imposes difficulty in the drone's controller design. This paper aims to achieve simultaneously precise tracking of trajectories and minimization of energy dissipation by the UAV's rotors. To this end elaborated control methods have to be developed.

A solution of the nonlinear control problem of tilt-rotor UAVs is attempted using a novel nonlinear optimal control method. This method is characterized by computational simplicity, clear implementation stages and proven global stability properties. At the first stage, approximate linearization is performed on the dynamic model of the tilt-rotor UAV with the use of first-order Taylor series expansion and through the computation of the system's Jacobian matrices. This linearization process is carried out at each sampling instance, around a temporary operating point which is defined by the present value of the tilt-rotor UAV's state vector and by the last sampled value of the control inputs vector. At the second stage, an H-infinity stabilizing controller is designed for the approximately linearized model of the tilt-rotor UAV. To find the feedback gains of the controller, an algebraic Riccati equation is repetitively solved, at each time-step of the control method. Lyapunov stability analysis is used to prove the global stability properties of the control scheme. Moreover, the H-infinity Kalman filter is used as a robust observer so as to enable state estimation-based control. The paper's nonlinear optimal control approach achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs. Finally, the nonlinear optimal control approach for UAVs with tilting rotors is compared against flatness-based control in successive loops, with the latter method to be also exhibiting satisfactory performance.

So far, nonlinear model predictive control (NMPC) methods have been of questionable performance in treating the nonlinear optimal control problem for tilt-rotor UAVs because NMPC's convergence to optimum depends often on the empirical selection of parameters while also lacking a global stability proof. In the present paper, a novel nonlinear optimal control method is proposed for solving the nonlinear optimal control problem of tilt rotor UAVs. Firstly, by following the assumption of small tilting angles, the state-space model of the UAV is formulated and conditions of differential flatness are given about it. Next, to implement the nonlinear optimal control method, the dynamic model of the tilt-rotor UAV undergoes approximate linearization at each sampling instance around a temporary operating point which is defined by the present value of the system's state vector and by the last sampled value of the control inputs vector. The linearization process is based on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modelling error, which is due to the truncation of higher-order terms from the Taylor series, is considered to be a perturbation that is asymptotically compensated by the robustness of the control scheme. For the linearized model of the UAV, an H-infinity stabilizing feedback controller is designed. To select the feedback gains of the H-infinity controller, an algebraic Riccati equation has to be repetitively solved at each time-step of the control method. The stability properties of the control scheme are analysed with the Lyapunov method.

There are no research limitations in the nonlinear optimal control method for tilt-rotor UAVs. The proposed nonlinear optimal control method achieves fast and accurate tracking of setpoints by all state variables of the tilt-rotor UAV under moderate variations of the control inputs. Compared to past approaches for treating the nonlinear optimal (H-infinity) control problem, the paper's approach is applicable also to dynamical systems which have a non-constant control inputs gain matrix. Furthermore, it uses a new Riccati equation to compute the controller's gains and follows a novel Lyapunov analysis to prove global stability for the control loop.

There are no practical implications in the application of the nonlinear optimal control method for tilt-rotor UAVs. On the contrary, the nonlinear optimal control method is applicable to a wider class of dynamical systems than approaches based on the solution of state-dependent Riccati equations (SDRE). The SDRE approaches can be applied only to dynamical systems which can be transformed to the linear parameter varying (LPV) form. Besides, the nonlinear optimal control method performs better than nonlinear optimal control schemes which use approximation of the solution of the Hamilton–Jacobi–Bellman equation by Galerkin series expansions. The stability properties of the Galerkin series expansion-based optimal control approaches are still unproven.

The proposed nonlinear optimal control method is suitable for using in various types of robots, including robotic manipulators and autonomous vehicles. By treating nonlinear control problems for complicated robotic systems, the proposed nonlinear optimal control method can have a positive impact towards economic development. So far the method has been used successfully in (1) industrial robotics: robotic manipulators and networked robotic systems. One can note applications to fully actuated robotic manipulators, redundant manipulators, underactuated manipulators, cranes and load handling systems, time-delayed robotic systems, closed kinematic chain manipulators, flexible-link manipulators and micromanipulators and (2) transportation systems: autonomous vehicles and mobile robots. Besides, one can note applications to two-wheel and unicycle-type vehicles, four-wheel drive vehicles, four-wheel steering vehicles, articulated vehicles, truck and trailer systems, unmanned aerial vehicles, unmanned surface vessels, autonomous underwater vessels and underactuated vessels.

The proposed nonlinear optimal control method is a novel and genuine result and is used for the first time in the dynamic model of tilt-rotor UAVs. The nonlinear optimal control approach exhibits advantages against other control schemes one could have considered for the tilt-rotor UAV dynamics. For instance, (1) compared to the global linearization-based control schemes (such as Lie algebra-based control or flatness-based control), it does not require complicated changes of state variables (diffeomorphisms) and transformation of the system's state-space description. Consequently, it also avoids inverse transformations which may come against singularity problems, (2) compared to NMPC, the proposed nonlinear optimal control method is of proven global stability and the convergence of its iterative search for an optimum does not depend on initialization and controller's parametrization, (3) compared to sliding-mode control and backstepping control the application of the nonlinear optimal control method is not constrained into dynamical systems of a specific state-space form. It is known that unless the controlled system is found in the input–output linearized form, the definition of the associated sliding surfaces is an empirical procedure. Besides, unless the controlled system is found in the backstepping integral (triangular) form, the application of backstepping control is not possible, (4) compared to PID control, the nonlinear optimal control method is of proven global stability and its performance is not dependent on heuristics-based selection of parameters of the controller and (5) compared to multiple-model-based optimal control, the nonlinear optimal control method requires the computation of only one linearization point and the solution of only one Riccati equation.

The essence of the conceptual design is getting the innovative projects or ideas to ensure the products with best performance. It has been proved that the theory of inventive problem solution (TRIZ) is a systematic methodology for innovation. The purpose of this paper is to illustrate the design of an adaptive robotic gripper as an engineering example to show the significance and approaches of applying TRIZ in getting the creative conceptual design ideas.

Gripping and holding of objects are key tasks for robotic manipulators. The development of universal grippers able to pick up unfamiliar objects of widely varying shapes and surfaces is a very challenging task. The requirement for new adaptive grippers is the ability to detect and recognize objects in their environments.

The main aim of this work is to show a systematic methodology for innovation as an effective procedure to enhance the capability of developing innovative products and to overcome the main design problems. The TRIZ method will be utilized in order to eliminate the technical contradictions which appear in the passively adaptive compliant robotic gripper.

The design of an adaptive robotic gripper as an engineering example is illustrated in this paper to show the significance and approaches of applying TRIZ in getting the creative conceptual design ideas.

The purpose of this study is to provide a novel multi-fingered hand made of hyperelastic material. This kind of hand has the advantage of less mechanical parts, simpler control system. It can greatly cut down the complexity and cost of the hands under conditions of ensuring enough flexibility of grasping.

Based on the principle of virtual work, the equations of pulling force and grasping force are derived. To get the max grasping force, the optimal structural dimensions of the hand are obtained by finite element simulations. Hand’s grasping experiment is conducted.

The factors influencing grasping force and grasping stability are identified, and they are the length between short poles around the knuckles and the height of short poles. Experimental results show that the max strain of knuckles is less than the elastic limit of hyperelastic material, and the presented hand is practicable. The adaptive ability and grasping stability of the presented hand are demonstrated.

A novel multi-fingered hand made of hyperelastic material is presented in this paper. By designing the thickness of every section of a hyperelastic plate, the knuckle sections will bend and other sections of the plate will remain straight, and thus, the multi-fingered hand will grasp.

Adaptive grippers are versatile end effectors that mechanically adapt their shapes to the objects they seize, allowing for soft and delicate grasps while still allowing for strong contact forces if needed and therefore they are well suited for industrial applications. The purpose of this paper is to present a software‐oriented approach to design optimal architectures of linkage‐driven adaptive (often a.k.a underactuated) fingers with three degrees of freedom.

The user of the software presented in this paper can design planar underactuated fingers following defined constraints. The software uses an algorithm able to compute the internal and contact forces generated, respectively, in and by the finger, it is also capable of automating the design of non‐straight links to eliminate mechanical interferences, and includes results from a topological synthesis to generate all possible architectures. The mechanisms are evaluated for many criteria such as the volume of their workspaces, stability, force isotropy, stiffness of their grasps, and compactness.

This article introduces 11 new designs of underactuated fingers for four different usages, and many of these variants are good candidates for a physical realization. One of the interesting results of this work is the recurrence of S3 variants coupled with torque amplifiers or closely resembling designs using many unrelated performance criteria.

This paper is the first, to the best of the authors' knowledge, to investigate the systematic design of underactuated fingers driven by linkages considering not one but dozens of mechanical architectures.

The purpose of this paper is to develop an automated industrial robotic system for handling steel castings of various sizes and shapes in a foundry.

The authors first designed a prismatic gripper for pick-and-place operations that incorporates underactuated passive hydraulic contact (PHC) phalanges that enable the gripper to easily adapt to different casting shapes. The authors then optimized the gripper parameters and compared it to an adaptive revolute gripper using two methods: a planar physics based quasistatic simulation that accounts for object dynamics and validation using physical prototypes on a physical robot.

Through simulation, the authors found that an optimized PHC gripper improves grasp performance by 12 per cent when compared to an human-chosen PHC configuration and 60 per cent when compared to the BarrettHand™. Physical testing validated this finding with an improvement of 11 per cent and 280 per cent, respectively.

This paper presents for the first time optimized prismatic grippers which passively adapt to an object shape in grasping tasks.

This paper aims to propose a novel hand to bridge the gap between the traditional rigid robot hands and the soft hands to obtain a better grasping performance.

The proposed hand consists of three fingers. Each finger has 15 degrees of freedom and three phalanxes, which can bend in one direction when load is applied, but they are rigid toward the opposite direction at the initial position. The grasping process and simulations of the fingers are discussed in this paper. Both kinematic and dynamics analyses are performed to predict the performance of the hand. Subsequently, a prototype of the hand is developed for experiments.

Both kinematics and dynamics analyses indicate good grasping performance of the hand. Simulations and experiments confirm the feasibility of the finger design. The hand can execute hybrid grasping modes with more uniform force distribution and a larger workspace than traditional rigid fingers. The proposed hand has much potential in the industrial sector.

A new method to obtain better grasping performance and to bridge the gap between the rigid finger and the soft finger has been presented and verified. The hand combines the advantages of both the rigid phalanxes and the soft fingers. Compared with some traditional rigid fingers, the proposed design has a more uniform force distribution and a bigger workspace.

The capability to perform dexterous operations in an autonomous manner would greatly enhance the productivity of robotic operations. In this paper, we present a new methodology for vision‐based grasping of objects or parts using a three‐finger hand as a gripper of a robotic manipulator.

The hand employed in our work, called SARAH, was designed for robotic operations on the space station, however, the main steps of our procedure can be applied for tasks in a manufacturing environment. Our methodology involves two principal stages: automatic synthesis of grasps for planar and revolute objects with SARAH and vision‐based pose estimation of the object to be grasped. For both stages, we assume that a model of the object is available off‐line.

In the paper, numerical results are presented for grasp synthesis of several objects with SARAH to demonstrate the feasibility and optimality of the synthesized grasps. Experimental results are also obtained with SARAH as the end‐effector of a seven‐degree‐of‐freedom robotic arm, demonstrating the feasibility of the integrated vision‐based grasping.

The methodology described in the paper, although represents a substantial step towards automated grasping with a robotic manipulator, still requires some decision making from the user. Further work can improve the pose identification aspects of the algorithm to make them more robust and free of human intervention. As well, the grasp synthesis procedure can be expanded to handle more complex and possibly moving objects, as well as to allow for different grasp types than those considered here.

The work demonstrates feasibility of autonomous grasp execution in industrial setting by using a three‐finger hand as a robotic gripper.

The results presented in the paper demonstrate the feasibility of synthesising optimised grasps which take into account the kinematics of the gripper. We also demonstrate a real implementation of vision‐based grasping by using a robotic manipulator with a three‐finger hand.