Universal grasping for a diverse range of objects is a challenging problem in robotics, especially in the presence of mixed properties with fragile/rigid and heavy/light. Toward universal grasping, this article presents a practical and systematic grasping control framework that enables a variable stiffness gripper to handle the objects with diverse properties using a category-aware force regulation approach, termed classification-based force grasping. Under this framework, a convolutional neural network (CNN) is employed to classify the category of the grasping object, and a grasping force is determined based on the classified category through a database that records a predefined force magnitude per category. Sequentially, the gripper can be adjusted to a force-optimized stiffness, which facilitates the achievement of an accurate grasping force regulation in a large range. Technically, two novel enabling modules are developed for grasping classification and execution, respectively. First, a novel weight imprinting technique based on center-guided feature embedding is proposed for object classification. It enables the CNN to efficiently handle novel object categories using only a few samples even without retraining/fine-tuning. Second, a vision-based grasping force sensing module is developed, which takes advantage of the specifically designed variable-stiffness gripper. Its grasping force can be estimated from the deflection angle of finger flexure by the vision so that the contact force can be sensed and regulated. Remarkably, only single-source vision information is needed for both of the above modules without any additional force sensor. Experiments are conducted extensively to evaluate the performance of the proposed force grasping approach.Note to Practitioners—Robotic grasping often needs to handle novel categories of objects. As a result, frequent retraining of the classification neural network is a pain point, which is tedious and prone to overfitting with only a few samples. In this work, metric learning is introduced for grasping classification where a novel kind of weight imprinting classification is proposed to handle the novel classes by better feature embedding and directly setting the classifier weights without retraining or fine-tuning. Together with the benefits from the variable stiffness feature of the gripper, the proposed vision-based force grasping approach can handle a wide range of objects from fragile to heavy, and the grasping force is controllable from 0.2 N onward to the motor limitation. The controllable grasping force resolution of the proposed vision grasping is better than 0.05 N, the accuracy of the grasping force is evaluated from 0.2 to 12 N, and the evaluated grasping objects are from extremely fragile potato chips and eggshell to heavy flange and metal block.

Data-efficient domain adaptation with only a few labelled data is desired for many robotic applications, e.g., in grasping detection, the inference skill learned from a grasping dataset is not universal enough to directly apply on various other daily/industrial applications. This paper presents an approach enabling the easy domain adaptation through a novel grasping detection network with confidence-driven semi-supervised learning, where these two components deeply interact with each other. The proposed grasping detection network specially provides a prediction uncertainty estimation mechanism by leveraging on Feature Pyramid Network (FPN), and the mean-teacher semi-supervised learning utilizes such uncertainty information to emphasizing the consistency loss only for those unlabelled data with high confidence, which we referred it as the confidence-driven mean teacher. This approach largely prevents the student model to learn the incorrect/harmful information from the consistency loss, which speeds up the learning progress and improves the model accuracy. Our results show that the proposed network can achieve high success rate on the Cornell grasping dataset, and for domain adaptation with very limited data, the confidence- driven mean teacher outperforms the original mean teacher and direct training by more than 10% in evaluation loss especially for avoiding the overfitting and model diverging.

This paper presents a novel structure-controlled variable stiffness robotic gripper that enables adaptive gripping of soft and rigid objects with a wide range of compliance. With the structure-controllable principle, the stiffness is controlled by the mechanical structure configurations rather than by material properties or electronic means. The principle is realized by changing the effective second moment of area of the gripper finger through rotating a built-in flexure hinge shaft. Based on this principle, the states of the stiffness can be continuously, instead of discretely, studied and assessed over the intermediate states from compliant to almost completely rigid. A variable stiffness mechanism has been developed to demonstrate the validity of the proposed principle. It enables that the finger stiffness and gripping position are independently controlled. With the introduction of flexure hinges, the undesired lateral buckling resulted from the rotation of a normal leaf spring is eliminated. In addition, a two-finger parallel gripper with this variable stiffness mechanism is developed which can provide the grasping stiffness according to the grasping task requirements. The effectiveness of the gripper has been demonstrated to handle the objects range from light, fragile to heavy, rigid without using any feedback loop or soft pads.

This paper presents a new variable stiffness actuator (VSA) based on a structure-controlled method: controlling the mechanical structure of the actuator by rotating four flexure hinges. The VSA possesses a property that the output position and stiffness are independently controlled. This is realized by a serial arrangement of a principle driving motor, a small stiffness variation motor and a novel variable stiffness mechanism (VSM). The VSM consists of four combined notch flexure hinge frames, each of which contains an inner rotary flexure shaft and outer stationary hinge housing. The stiffness is adjusted by rotating the inner flexure shaft to change the second moment of area. Its value is independent to the VSA output angle when the flexure rotational angle is fixed. The working principle of this VSA is elaborated and the optimization mechanical design of the VSM is presented. A prototype has been implemented and its primary characteristic test results validate the design features.

This paper presents a novel sampling-based motion planning method for shape inspection applications with a redundant robotic system. In this paper, a 7-Degree-of-Freedom (DOF) redundant robotic system consisting of a 6-DOF manipulator and a 1-DOF turntable is used for the industrial inspection problem. A Set Covering Problem (SCP) is formulated to select suitable viewpoints that satisfy the inspection requirements, and a Generalized Travelling Salesman Problem (GTSP) is formulated to determine both the robot poses and the visiting sequences. While previous studies solve the two problems separately, we formulate the SCP and GTSP problems as a combined sequencing SC-GTSP problem. A Random-Key Genetic Algorithm (RKGA) is then used to solve the combined SC-GTSP problem in a one-step optimization process. To validate the effectiveness of our method, we applied the proposed method to several motion planning cases. The results show that the proposed method outperforms the previous approaches by requiring up to 28.1% less total inspection time.

This paper presents a novel view planning method to generate suitable viewpoints for the reconstruction of the 3D shape of buildings, based on publicly available 2D map data. The proposed method first makes use of 2D map data, along with estimated height information, to generate a rough 3D model of the target building. Randomized sampling procedures are then employed to generate a set of initial candidate viewpoints for the reconstruction process. The most suitable viewpoints are selected from the candidate viewpoint set by first formulating a modified Set Covering Problem (SCP) which considers image registration constraints, as well as uncertainties present in the rough 3D model. A neighborhood greedy search algorithm is proposed to solve this SCP problem and select a series of individual viewpoints deemed most suitable for the 3D reconstruction task. The paper concludes with both computational and real-world field tests to demonstrate the overall effectiveness of the proposed method.

Linear direct feed drives are widely used in machine tools, but an abrupt counter force from the secondary part will induce the jerk to the metro frame contacted with the linear motor and cause the vibration of auxiliary devices on it. The jerk-decoupling cartridge (JDC) provides a buffer to reduce such an impact. To systematically take care of both the tracking error and the jerk induced to the metro frame, this paper presents an integrated design approach to determine parameters in the JDC and the position controller of the feed drive. The initial formulated non-convex optimization problem is converted to convex constrained gradient optimization problem and linear step searching problem. Thus, fast convergence of parameters is achieved within first few iterations. Through a series of simulation, the effectiveness of proposed methodology is verified.

The view planning problem is the problem that involves finding suitable viewpoints for vision-related tasks such as inspection or reconstruction. In this paper, we propose a novel view planning algorithm for a camera-equipped Unmanned Aerial Vehicle (UAV) acquiring visual geometric information of target objects in its surrounding environment. The proposed model-based approach makes use of iterative random sampling and a probabilistic potential-field method to generate candidate viewpoints in a non-deterministic manner. Combinatorial optimization is then applied to select the most suitable subset of these candidate viewpoints to complete the given visual inspection or shape reconstruction task. The effectiveness of the proposed method is demonstrated through a number of computational tests that compare its overall performance against two previous methods. A field-test is also performed to demonstrate the method's applicability in a real world UAV-based shape reconstruction task of an outdoor statue.

This paper presents a new flexible fixtureless assembly (FFA) approach for building T-joint structures automatically. The method is based on a Fixturing Assistive Gripper (FAG) mounted on a robot arm for forming T-joint sections. It eliminates possible uncertainties in terms of positioning and size errors during fit-up process. The method is verified by a robotic assembly workcell which includes dual robots and a simple machine vision unit. The basic algorithms for image processing, task planning, dual robot cooperative motion and path planning are developed for assembling a simple structure which predominantly formed by T-joint sections. Experiments show that the workcell can effectively eliminate the alignment error and successfully complete T-joint assembly task without the complicated sensing system typically required in the existing approaches.

A flexure-based parallel manipulator (FPM) is a closed-loop compliant mechanism in which the moving platform is connected to the base through a number of flexural legs. Utilizing parallel-kinematics configurations and flexure joints, the FPMs can achieve extremely high motion resolution and accuracy. In this work, we focus on the analysis and design of a 3-DOF (θx- θy- Z) zero-torsion FPM for nano-alignment applications. Among various possible zero-torsion parallel kinematics configurations, it is identified that the 3-legged Prismatic-Prismatic-Spherical (3PPS) is a suitable candidate. Based on the concept of instantaneous rotation, the critical kinematic design issues, such as displacement and workspace analyses, are addressed. With these analysis algorithms, the major kinematic parameters are readily determined to meet the task requirements. To achieve a large workspace, beam-based flexure joints are employed in the FPM design. As the beam based Universal (U) flexure joints are able to accommodate the required passive prismatic and spherical motions, each flexure PPS leg can be replaced by a simple flexure PU leg. A research prototype of the 3-DOF 3PU FPM has been developed, which achieves position and orientation resolutions of 20 nm and 0.05 arcsecond throughout a workspace of 5° × 5° × 5 mm, respectively.

This paper presents the design of a novel 4-DOF (x-y-θx-θy) flexure-based system used for coaxial alignment. The movable head (a rigid rod) of the system is suspended with two monolithic flexural mechanisms constructed with leaf flexures. To achieve the required x-y-θx-θymotion, the leaf-type flexures are specially arranged in such a configuration that is compliant in the specified axes but stiff in other axes. The leaf flexures are initially designed based on the linear models of the flexible beam deflection and then improved through FEA simulations. A system prototype was built with the flexural mechanisms. It demonstrates superior motion performances in the x and y axes as well as the angular axes. The prototype has been successfully applied in the coaxial alignment of the capillary machining.

Thermally induced deformation has become more of a concern for precision machines as accuracy is getting more stringent. Unlike other indirect drives which are possible to isolate or place rotating motors, which are heat sources, away from the working area. A linear motor is a direct drive system which is heat source and placed near to the working area. Therefore, this thermal effect characteristic study is conducted here to find out the effect of heat that is transferred and dissipated around the working area, causing unwanted deformation. The surface area joining the linear motor coil to the application carriage is large. It will be inaccurate to assume a constant temperature or heat flux through the entire surface. The temperature of the surface is different for different location and time. Experiments are conducted to investigate the surface temperature and heat flux profile in different application processes. Finally, the result of this investigation can define the heat source accurately so that a further study could develop a prediction scheme for the deformation of the carriage. This finding can be applied to error budgeting for machine design stages.

In this paper, we report our investigation on the force-induced responses of zebrafish chorion before and after being perturbed by an externally applied prescribed force. Our experimental results show that application of an external force leads to a reduction in the stiffness of the zebrafish chorion, and that variation in such a reduction is strongly influenced by the perturbation time. Our results provide evidence supporting the hypothesis that the stiffness of some cellular organism may be modified by the controlled application of an appropriate mechanical force, and demonstrate the potential of force-feedback control in micro/nano-manipulation as a promising engineering technique for studying disease properties and manipulating cellular biological functions.

This paper presents an approach to optimize the zebrafish-embryo microinjection process by selecting suitable speed trajectories for the motion of the micropipette, with the objective of minimizing the risk of damaging the embryo during the microinjection process. A viscoelastic model of a zebrafish embryo is developed based on experimental data. The speed optimization problem is formulated based on this viscoelastic model. Simulation results indicate that there exists an optimal speed trajectory for the micropipette under certain conditions. The key benefit of this speed optimization approach is that the turgor pressure inside the membrane is prevented from increasing significantly during the microinjection process, thus avoiding damaging the biological components in the embryo.

This paper presents the modeling and control of a Flexure-Based Electromagnetic Linear Actuator (FELA) that is employed as a high-precision imprinting actuator of a desktop hot-embossing imprinter. In this work, a systematic approach of obtaining the unknown physical parameters of FELA is presented. Subsequently, these parameters are used to design two model-based PID controllers that allow the FELA to perform high-precision positioning tasks and direct-force imprinting tasks respectively. As the imprinting tasks require the FELA to operate in both position and direct-force control modes, two types of control strategies are explored and their competency of enabling the FELA to perform such tasks are investigated. Lastly, the selected control strategy is implemented on the FELA to assist the hot-embossing imprinter in fabricating micro-channels on polymer substrates via a hot-embossing process.

This paper presents a ball-joint-like three-degree-of-freedom (3-DOF) permanent magnet (PM) spherical actuator which features a ball-shaped rotor with multiple PM poles and a spherical iron stator with air-core coils. Torque output of this PM spherical actuator is formulated analytically. Based on the torque model, simulation result of the actuator torque variation is presented. In addition, the effect of the stator iron on the torque output is evaluated.

This paper presents the kinematic calibration of a novel 7-degree-of-freedom (DOF) cable-driven robotic arm (CDRA), aimed at improving its absolute positioning accuracy. This CDRA consists of three 'self-calibrated' cable-driven parallel mechanism (CDPM) modules. In order to account for any kinematic errors that might arise when assembling the individual CDPMs, a calibration model is formulated based on the local product-of-exponential formula and the measurement residues in the tool-tip frame poses. An iterative least-squares algorithm is employed to identify the errors in the fixed transformation frames of the sequentially assembled 'self- calibrated' CDPM modules. Both computer simulations and experimental studies were carried out to verify the robustness and effectiveness of the proposed calibration algorithm. From the experimental studies, errors in the fixed kinematic transformation frames were precisely recovered after a minimum of 15 pose measurements.

A key process in assembly of microelectromechanical systems optical switches is of inserting fibers into U-grooves in silicon substrate. Due to positioning errors and dimensional tolerances in components, heavy collision occurs between fibers and the edges of U-grooves during insertion, throwing out fibers from the fiber holder or worse, damaging the components. Typical solutions to the problem involve determining errors using machine vision or force sensors, and then positioning fibers accurately by virtue of high precision multi-axis systems (with submicron repeatability). However, these approaches are costly and difficult to implement. In this paper, we present a low-cost passive assembly method to solve the problem. It utilizes a special flexure-based fixture to regulate high contact forces and accommodate assembly errors. Specifically, we model the problems happening in the process of fiber insertion and characterize the conditions of successful insertion. We then suggest how to design flexural fixtures so that the required insertion conditions can be met. Experimental results show that using such a fixture the fiber assembly can be successfully implemented even if the assembly system's accuracy is lower than 12 in and axes, and 0.07 in theta axis. These requirements are within the reach of most low-cost precision systems.

The microinjection is a common technique in genetic engineering for transferring genetic material into a cell. It is normally performed on a micromanipulation system that usually consists of an inverted microscope, a micromanipulator, a micropipette and an injector. Manual microinjection is a conventional and widespread practice. However, this approach suffers from low success rate, poor efficiency, and high probability of contamination. We have developed a micromanipulation system for automatic batch microinjection by automating the key process of penetration in a microinjection. The microinjection system automatically identifies and penetrates each embryo/cell with a constant and fast speed, and in doing so, eliminates the possibility of contamination caused by manual operations. The effectiveness of this force-controlled system has been experimentally demonstrated in the tasks of automatic identification and penetration zebrafish embryos, which are widely used as a model for studying vertebrate development and genetics.

This paper presents the joint centre self-identification of a novel cable-driven anthropocentric shoulder rehabilitator. For such a wearable rehabilitator, identification of joint centre is critical for kinematic modeling, path planning and motion control. However, the shoulder joint centre location is unknown when a user wears this rehabilitator and it differs among users. These complicate the initial patient preparatory. A joint centre self-identification model is formulated based on the differential change in the cable end-point distance. A computationally effective algorithm is employed to identify the shoulder joint centre. It does not require any external measurement devices because of the redundant actuation scheme in the cable-driven shoulder rehabilitator. In order to verify the effectiveness and robustness of the proposed algorithm, we conducted computer simulation studies. In the simulation example, although large errors (up to plusmn50mm) had been injected into the initial estimates, the joint centre was always accurately identified within four to five iterations.

Manipulation tasks performed under microscopes are fatigue inducing on account of the difficulty in visualisation of the scene and hand-eye coordination. This work concentrates on providing assistance to the operator in the form of a visual-haptic interactive system which allows intuitive command of the manipulator motion axes. Specific examples of visualisation tools are presented which compensate for problems such as: spatial d is orientation, loss of depth perception, and occluded data.

This paper presents a novel flexural-based nano-positioning actuator that has a positioning accuracy of 10 nm (limited by encoder resolution) throughout a range of 3 mm. A new dual-magnet configuration is introduced to enhance this electromagnetically driven actuator in achieving 60 N/Amp in a compact configuration. In addition, a constant and evenly distributed magnetic flux density is obtained throughout 11 mm of air gap. A new mathematical model is presented to accurately predict the behavior of magnetic field within the effective air gap of this configuration. Complete analytical models for this actuator's electromagnetic drive and flexural-bearing support element are presented. Lastly, a prototype of this actuator is developed for validating the established analytical models and verifying the claimed capabilities.

The orifice type of aerostatic bearings have been used for precision machine. However, most of researchers are focus on the dynamic and stability analyses of aerostatic bearings instead of the design and development. This paper provides the basic frame work and the procedure for design and development of aerostatic bearings with the result from the experiment and finite element analysis. The finite element method is employed to obtain the numerical solution of the pressure distribution and the flow speed between the surface of aerostatic bearing and the slide surface. It can provide the information between the input pressure and the output pressure. The experiment includes the physical measurement of the air pressure on the aerostatic bearing and the stiffness and damping characteristics. This result can help the researchers and engineers to further understand the basic characteristics of aerostatic bearings and correct the design the aerostatic bearing for their application

An operational space dynamic model of a redundantly actuated wheeled mobile robot taking into account the wheel-ground interaction is derived based on vehicle dynamics. The conditions for the robot to avoid slip are derived for both torque and motion. Two torque distribution schemes based on different criteria are proposed. The non-slip condition for motion is utilized to plan slip avoidance paths. The null space joint torques are utilized to fulfil the non-slip condition for torque and avoid actuator torque limits violation. Simulations results are presented to demonstrate the effects of wheel-ground interaction and performance of the proposed torque distribution schemes

This paper presents a design concept of spherical actuators including a ball-shaped rotor with two layers of permanent-magnet (PM) poles and a spherical-shell-like stator with two layers of circumferential air-core coils. Corresponding to the poles configuration, the torque model of the spherical actuator has been derived. The magnetic field as well as torque output have been compared with that of spherical actuator with single-layer PM-pole configuration. This generic torque modeling method can be extended for spherical actuators with multi-layer PM&coil poles which can achieve high motion resolution as well as large working range

An actuator with 3-DOF spherical motion is developed based on layered arrangement of stator coils and rotor poles. Due to the use of air-core coils and permanent magnet poles, the torque model of the actuator cannot be obtained by traditional coenergy approach. This paper describes a generic torque modeling method based on Lorentz force law. The closed-form solution of the torque model is derived from the scalar potentials of the magnetic field. Experimental study on the torque model is carried out. A comparison between the closed-form solution and the experimental result shows that the proposed torque model is valid and can be used for real-time control.

This paper has proposed a design concept of a spherical actuator including a ball-shaped rotor with a full circle of permanent-magnet (PM) poles and a spherical-shell like stator with two layers of circumferential air-core coils. One key feature of this design is parameterization of the PM pole, which benefits the design optimization of the spherical actuator greatly. According to the magnetic field model, the variation of flux density with respect to PM-pole parameters can be revealed. Therefore, these parameters can be appropriately chosen to achieve a high magnetic flux density. Another advantage of this design is the singularity-free, which is verified within the workspace with torque model and condition numbers.

Based on the local product-of-exponentials (POE) formula, this paper proposes an effective approach to solve the inverse displacement analysis for a class of modular 3-legged parallel robots by Paden-Kahan sub-problems. Since passive joint displacements can be solved together with solving active joint, so that the solved passive joint displacements can be regarded as guess solution to calculate forward kinematics by traditional numerical solution method. Through comparing with traditional iterative numerical solution method, proposed approach can evidently improve computation efficiency for forward kinematics. The effectiveness of the proposed approach has been demonstrated by machining demonstrations with online motion monitoring for a workpiece with spherical surface.

This paper presents the development of a digital signal processor (DSP) based motion controller for a linear servo motor system. The linear motor system employs a moving magnet non-commutated DC linear servo motor as the actuator, and a linear variable differential transformer (LVDT) as the position feedback transducer. It is ideal for short stroke, high accuracy and high speed closed loop servo applications. The controller hardware is based on a TI TMS320LF2407A DSP. The system architecture and motion control strategies are presented. An index motion is implemented using this system. The experimental results with discussions are also given.

The design of a new six-degree-of-freedom (6-DOF) parallel-kinematics machine (PKM) has been proposed. Different from the conventional Stewart-Gough platform which has six extensible legs, the new PKM employs three identical RPRS legs to support the moving platform. Since all joint axes, excluding the three spherical joints at the leg ends, are parallel to each other and perpendicular to the base plane, this 6-DOF PKM presents a promising platform structure with decoupled-motion architecture (DMA) such that translation in a horizontal plane and rotation about a vertical axis are driven by the three active revolute joints, while translation in the vertical direction and rotation about horizontal axes are driven by the three active prismatic joints. As a result, this 6-DOF 3RPRS PKM with DMA has simple kinematics, large cylindrical reachable workspace, and high stiffness in the vertical direction. These features make it appropriate for light machining and heavy parts assembly tasks. Because of the DMA, a projection technique is employed for its kinematics analysis. By projecting the manipulator onto horizontal directions and vertical planes, the kinematics issues such as the displacement, singularity, and workspace analysis are significantly simplified.

Focusing on the instantaneous velocities of passive joints, a formulation approach is proposed for the instantaneous kinematics and singularity analysis of a class of three-legged parallel robots. Since only four 3/spl times/3 matrices need to be analyzed, the complexity of singularity analysis is significantly, reduced. Using the product-of-exponentials (POE) formula, the kinematic equations possess well-defined algebraic structures so that the instantaneous kinematics and singularity analysis algorithms can be readily and systematically formulated. Three types of singularities, i.e. the forward, inverse, and combined singularities, have been identified. A unified condition for various singularities is proposed. Significant geometric conditions are also presented for identifying singularity configurations that require simple computations.

This paper details the design of a novel robotic system for performing automated container case packing operations. The system has unique design concepts that addressed many real problems generally encountered in bottle packing operations. The efficient automated operation is mainly achieved through the use of dual-arm concept for parallel tasking. While one arm is searching and picking up a group of bottles, the other arm orientates and loads the bottle(s) into the carton box container. The picking arm is equipped with a range sensor that allows a closed-loop system for compensating position errors of the bottles. Two types of grippers are designed for handling a wide range of bottle sizes and assembly layouts providing automation flexibility. In order to achieve a high degree of automation, the picking arm is incorporated with a layer separator removal module. As a result, no human intervention is required when one layer of bottles is finished in the bottle pallet. In the course of developing the system, robotic simulation technology is used for evaluating the design concepts as well as for determining the specifications of the actuators.

The closed-loop structure of a parallel robot results in complex kinematic singularities in the workspace of the mobile platform. Singularity analysis become important in design, motion planning, and control of parallel robots. Focusing on the instantaneous velocities of passive joints, a new formulation approach is proposed for the instantaneous kinematics and singularity analysis of a class of three-legged parallel robots. Excluding the passive spherical joints at the leg ends, the number of 1-dof passive joints in a three-legged, 6-DOF, parallel robot is three, which is only half of the number of active joints (six). Consequently, the complexity of the singularity analysis is significantly reduced because only four 3/spl times/3 matrices need to be analyzed. Using the product-of-exponential formula, the kinematic equations possess well-defined algebraic structures so that the instantaneous kinematics and singularity analysis algorithms can be readily and systematically formulated. Three types singularities, i.e., the forward, inverse, and combined singularities, have been identified. A unified condition for various singularities is proposed. Significant geometric conditions are also presented for identifying singularity configurations that requires simple computations.

Robot programming is a very tedious task that involves defining the relevant robot positions and configurations, and writing the robot program to execute the task. In this paper, we present an application of the control of the dynamic behavior of robotic manipulators to achieve walk-through programming of a powered arm. The algorithm is based on impedance control with zero stiffness to allow the robot to be moved by the human hand during walk-through teaching. We demonstrate the application using a welding robot we have customized and improved on for use in shipyards. We describe the architecture, our methodologies, the practical issues and present the results of our performance evaluation.