Artificially intelligent (AI), powerful, and reliable human–machine interfaces (HMIs) are highly desired for wearable technologies, which proved to be the next advancement when it comes to humans interacting with physical, digital, and mixed environments. To demonstrate them, here we report on an innovative noninvasive, lightweight, low-cost, wearable, and soft pressure-based force myography (pFMG) HMI in the form of an armband. The armband acquires stable mechanical biosignals in the form of air pressure information in response to forces induced by muscle activity consisting of contraction and relaxation that deform its pressure-sensitive chambers (PSCs). The PSCs are characterized by a fast response to a mechanical biosignal, negligible hysteresis, repeatability, reproducibility, reliability, stability, minimal calibration requirements, and durability (more than 1 500 000 cycles). The pFMG armband is resistant to sweat, body hair present on the skin, worn cloth, and scars, and resilient to external mechanical deformations. We demonstrate the capability and versatility of the pFMG-based HMI armband to interact with and control collaborative robot manipulators, robotic prosthetic hands, drones, computer games, and any system where humans are in the loop. The control signals are generated through the implementation of a machine learning algorithm to decode and classify the acquired biosignals of different hand gestures to rapidly and accurately recognize the intentions of a user. The easy and direct fabrication and customization of the armband in addition to its ability to decode any desired gesture rapidly and reliably based on stable and reliable biosignals makes it ideal to be integrated into AI-powered HMI applications.

In this study, a novel magnetically actuated robotic capsule (patent-filed, Alici and Zhou, 2019) is proposed for site-specific drug delivery inside the gastrointestinal tract. Retractable needles are equipped into the capsule-like robot to inject the drug directly into intended tissues, which will contribute to the full and fast absorption of the medication and consequently increase the efficacy of drug delivery. The needle is concealed inside the capsule initially and can be actively protruded and retracted by a magnetic membrane. A second magnetic membrane is employed to discharge the drug out of the reservoir and inject it into the targeted tissue through the needle. Besides active drug releasing, the robotic capsule is able to perform active locomotion controlled by an external magnet wirelessly. Theoretical and experimental analyses were conducted to characterize the magnetic membranes for the selections of these batteries-less soft actuators for wireless in-body drug injection. Both locomotion and drug injection tests were successfully performed with the prototypes inside the samples of the porcine small intestine, which validated the feasibility of the proposed drug delivery system.

This paper explores the design process of robotics and autonomous systems using a co-design approach, applied ethics, and values-driven methods. Specifically, the approach seeks to move beyond traditional risk assessment toward a greater consideration of end-user exposure. The goal of the ethics-based co-design approach is to identify end-user and stakeholder values that guide the minimization of end-user vulnerability associated with the employment of autonomous systems. This design process is also used to identify positive consequences that probably increase human well-being as opposed to simply avoiding harm. We argue that biomedical autonomous systems design, during the preclinical phase, should bring together diverse stakeholders that would not traditionally be involved in design. We also argue that embedding ethical considerations in the engineering design process should bring together a diverse range of stakeholders to more accurately appreciate possible end-user implications of a design. With complex systems design, such as biotechnologies, greater awareness is necessary of the ethical implications of designed autonomy to end-user exposure.

Numerous soft grippers have been developed based on smart materials, pneumatic soft actuators, and underactuated compliant structures. In this article, we present a three-dimensional (3-D) printed omni-purpose soft gripper (OPSOG) that can grasp a wide variety of objects with different weights, sizes, shapes, textures, and stiffnesses. The soft gripper has a unique design that incorporates soft fingers and a suction cup that operate either separately or simultaneously to grasp specific objects. A bundle of 3-D-printable linear soft vacuum actuators (LSOVA) that generate a linear stroke upon activation is employed to drive the tendon-driven soft fingers. The support, fingers, suction cup, and actuation unit of the gripper were printed using a low-cost and open-source fused deposition modeling 3-D printer. A single LSOVA has a blocked force of 30.35 N, a rise time of 94 ms, a bandwidth of 2.81 Hz, and a lifetime of 26 120 cycles. The blocked force and stroke of the actuators are accurately predicted using finite element and analytical models. The OPSOG can grasp at least 20 different objects. The gripper has a maximum payload-to-weight ratio of 7.06, a grip force of 31.31 N, and a tip blocked force of 3.72 N.

Using positron emission markers for the localization of a robotic capsule endoscope is promising because it does not require onboard space or built-in battery for operation. Further, its compatibility with magnetic actuation is another significant advantage compared with conventional magnetic localization methods reported in the literature. In this paper, we propose a new tracking algorithm based on rigid-body transformation and gamma rays emitted from three positron emission markers onboard to localize an endoscopic capsule operating within the gastrointestinal tract of the human body. Different from traditional rigid-body transformation based on datasets of 3-D points, our method estimates the transformation parameters (e.g., translation vector and rotation angle) from several groups of 3-D lines in order to determine the locations of the markers emitting the gamma rays. Validated by both simulation data using a voxelized phantom in the Geant4 Application for Emission Tomography toolkit and the experimental data collected from a positron emission tomography scanner, the new localization method shows a significant improvement in the tracking accuracy (an average position error of 0.4 mm and orientation error of 1.9°) and the failure rate (18/9600 localization runs), compared to the localization results reported in the literature.

Conventional robotics have always pursued methods to bring robots near human. Human robot interaction (HRI) has gained great momentum to realize freeing robots with various control methods to ensure their safe operations with human presence. Soft robotics, alternatively, focuses on building robots mainly made of low elastic moduli materials, which may not be capable of harming humans due to nature of the materials they are made of, nevertheless, requires stiffness augmentation to be able to transmit relatively higher forces. In this study, we designed and fabricated an underactuated soft robotic finger using fused deposition modelling type 3D printing with a thermoplastic elastomer material. Robotic finger is actuated with a tendon-cable attached to a linear servo-actuator while secondary linear servo-actuator is used to control position of a stiffness-enhancement unit made of bistable metal strips. In order to verify stiffness enhancement, we perform precise position control and estimate external disturbances. Experimental results suggest that estimated external disturbances (i.e. stiffness of soft robotic finger) change under the same position conditions (finger flexion) thanks to precise robust motion controller.

Soft robotics has recently gained a significant momentum as a newly emerging field in robotics that focuses on biomimicry, compliancy and conformability with safety in near-human environments. Beside conventional fabrication methods, additive manufacturing is a primary technique to employ to fabricate soft robotic devices. We developed a monolithic soft gripper, with variable stiffness fingers, that was fabricated as a one-piece device. Negative pressure was used for the actuation of the gripper while positive pressure was used to vary the stiffness of the fingers of the gripper. Finger bending and gripping capabilities of the monolithic soft gripper were experimentally tested. Finite element simulation and experimental results demonstrate that the proposed monolithic soft gripper is fully compliant, low cost and requires an actuation pressure below -100 kPa.

Robotic rehabilitation devices are more frequently used for the physical therapy of people with upper limb weakness, which is the most common type of stroke-induced disability. Rehabilitation robots can provide customized, prolonged, intensive, and repetitive training sessions for patients with neurological impairments. In most cases, the robotic exoskeletons have to be aligned with the human joints and provide natural arm movements. This is a challenging task to achieve for one of the most biomechanically complex joints of human body, i.e., the shoulder. Therefore, specific considerations have been made in the development of various existing robotic shoulder rehabilitation orthoses. Different types of actuation, degrees of freedom (DOFs), and control strategies have been utilized for the development of these shoulder rehabilitation orthoses. This paper presents a comprehensive review of these shoulder rehabilitation orthoses. Recent advancements in the mechanism design, their advantages and disadvantages, overview of hardware, actuation system, and power transmission are discussed in detail with the emphasis on the assisted DOFs for shoulder motion. A brief overview of control techniques and clinical studies conducted with the developed robotic shoulder orthoses is also presented. Finally, current challenges and directions of future development for robotic shoulder rehabilitation orthoses are provided at the end of this paper.

Robotic systems consisting of rigid elements connected to each other with single degree of freedom joints have been studied extensively. Robotic systems made of soft and smart materials are expected to provide a high dexterity and adaptability to their physical environment, like their biological counterparts. Electroactive polymer (EAP) actuators, also known as artificial muscles, which can operate both in wet and in dry environments with their promising features such as a low foot-print in activation and energy consumption, suitability to miniaturization, noiseless, and fully compliant operation can be employed to articulate a soft robotic system. This paper reports on kinematic modeling of a polypyrrole-based EAP actuator which is designed and fabricated to form helical configurations in 3-D from its initially spiral 2-D configuration. Denavit-Hartenberg transformations are combined with the backbone model of the actuator to establish the kinematic model. A parametric model has then been incorporated into the kinematic model to accurately estimate the helical configurations of the EAP actuator as a function of time under an electrical input. Experimental and simulation results, which are in good correlation, suggest that the proposed modeling approach is effective enough to estimate the 3-D helical configurations of the EAP actuator.

The wireless capsule endoscope (WCE) is a first-line medical tool for the diagnosis of many gastrointestinal (GI) tract diseases such as obscure GI bleeding, Crohn’s disease, small bowel tumors, and Celiac disease. Over the past few years, significant research attention has been paid to upgrading the WCE from a diagnostic-only tool to an active medical robot having not only diagnostic capabilities but therapeutic functionalities, such as biopsy, microsurgery, and targeted drug delivery, as well. One of the major limitations that impedes the development of such a robotic-type endoscope is the lack of a highly accurate localization system. In this paper, we present an experimental evaluation of a new real-time localization method (patent pending) based on tracking three positron emission markers embedded in the cover of an endoscopic capsule. Coincidence gamma rays emitted from the markers are detected by surrounding gamma ray detectors. The position and orientation information of the capsule can then be extracted by an effective tracking algorithm. The experiments were conducted in two different commercial positron emission technology (PET) scanners: Philips Allegro and Philips TF64. The experimental results show that the proposed localization method could provide less than 0.5-mm position error and$\hbox{2.4}^{\circ }$orientation error in a localization time interval of 50 ms with an average computational time of 6 ms per time interval. Zero power consumption and zero space occupation inside the capsule are additional advantages of this localization method.

This paper proposes and evaluates an adaptive technique and a variable structure control approach for piezoelectric actuation systems to track specified motion trajectories. The proposed control methodologies are formulated to accommodate unknown or uncertain system parameters, nonlinearities including the hysteresis effect, and external disturbances in the piezoelectric actuation systems without any form of feed-forward compensation. In this study, both control methodologies are demonstrated to possess a promising motion tracking ability experimentally. In comparison, the variable structure control approach is evaluated to be superior to the adaptive technique in the motion tracking control. With the ability to track motion trajectories under parametric uncertainties, nonlinearities, and external disturbances, the proposed control methodologies are very attractive in realising the high-precision piezoelectric actuation systems for micro/nano manipulation

This paper presents the direct kinematic solutions to 3DOF planar parallel mechanisms. Efforts to solve the direct kinematics of planar parallel mechanisms have concentrated on RPR mechanisms due to its inherent simplicity. It is established that the direct kinematic equations of a general 3DOF planar parallel mechanism can be reduced to a univariate polynomial of degree 8. This paper presents the derivation of this univariate polynomials for both 3RRR and 3RPR mechanisms, showing the similarities and differences between the two common configurations of 3DOF planar parallel mechanisms. This paper also presents the on the direct kinematic solution to a simplified case of the 3RRR planar parallel mechanisms, where it is possible to decouple the polynomial further into two quadratic equations, describing the position and orientation of the end-effector, respectively. This result will provide an efficient computation method for a very useful configuration of planar parallel manipulators

This paper proposes a robust control methodology for piezoelectric actuation systems to track specified motion trajectories. This is motivated by the search for an effective control strategy to deal with the problem of nonlinear behaviour in the piezoelectric actuation systems. The basic concept associated with this approach lies in the specification of a target performance and the formulation of a robust control scheme for the system to ensure the convergence of the position tracking error to zero in the presence of parametric uncertainties and hysteresis effect inclusive of other un-modelled disturbances. Stability of the control system is proven theoretically and the robust control methodology is demonstrated to possess a promising tracking ability through the control experiments. Implementation of the control law requires only a knowledge of the estimated parameters and their corresponding bounds as well as the bound of the hysteresis effect including disturbances. Being capable of handling uncertainties and disturbances, the robust control methodology is very attractive in the field of micro/nanomanipulation in which high-precision control applications could be realised

There has been an increasing interest in conducting polymers, especially polypyrrole (PPy), as potential actuators for many cutting edge applications including micromanipulation and biomedical devices. Their performance needs to be assessed in terms of force and displacement outputs before they can be employed in practical devices. As part of an ongoing project to develop a robotic gripper for micromanipulation/fabrication applications, this study focuses on (i) deriving a mathematical model to predict the force produced at the tip of a trilayer bending type PPy-based actuator under input voltages, and (ii) experimentally verifying the model. The model has been used to estimate the force produced by a robotic finger consisting of a PPy actuator and a rigid link. The results presented show a good agreement between the experimental and predicted forces for two actuators with the dimensions of (10 mm times 1 mm times 0.17 mm) and (5 mm times 1 mm times 0.17 mm) with driving voltages up to 0.8 V

This paper presents a new methodology to simulate soft object deformation by drawing an analogy between a cellular neural network (CNN) and elastic deformation. The potential energy stored in an elastic body as a result of a deformation caused by an external force is propagated among mass points by a nonlinear CNN. The novelty of the methodology is that: 1) CNN techniques are established to describe the potential energy distribution of the deformation for extrapolating internal forces and 2) nonlinear materials are modeled with nonlinear CNNs rather than geometric nonlinearity. Integration with a haptic device has been achieved for deformable object simulation with force feedback. The proposed methodology not only predicts the typical behaviors of living tissues, but it also accommodates isotropic, anisotropic, and inhomogeneous materials, as well as local and large-range deformation.

Piezoelectric actuators (PEA) are the fundamental elements for high-precision high-speed positioning/tracking task in many nanotechnology applications. However, the intrinsic hysteresis observed in PEAs has impaired their potential, specially, the motion accuracy. In this paper, the complicated nonlinear dynamics of PEA including hysteresis, creep, drift and time-delay etc. are treated as a black-box system exhibited as rate-dependent hysteresis. The multi-valued hysteresis is analyzed as a single-valued function so that a neural network (NN) can be built to model the hysteresis and its inversion. A sliding mode controller (SMC) augmented with inverse hysteresis model is then developed to compensate the hysteretic behavior, modeling error and disturbance to improve the positioning/tracking stability and accuracy. The effectiveness of this algorithm experimentally verified through the actual tracking control of a PEA.

This paper presents a new methodology for the deformation of soft objects by drawing an analogy between heat conduction and elastic deformation. The potential energy stored in an elastic body as a result of a deformation caused by an external force is propagated among mass points by the principle of heat conduction. An improved heat conduction model is developed for propagating the energy generated by the external force in a natural manner. A method is presented to derive the internal forces from the potential energy distribution. This methodology not only deals with large-range deformation, but also accommodates both isotropic and anisotropic materials by simply changing thermal conductivity constants. Examples are presented to demonstrate the efficiency of the proposed methodology.

This paper presents the enhanced stiffness modeling and analysis of robot manipulators, and a methodology for their stiffness identification and characterization. Assuming that the manipulator links are infinitely stiff, the enhanced stiffness model contains: 1) the passive and active stiffness of the joints and 2) the active stiffness created by the change in the manipulator configuration, and by external force vector acting upon the manipulator end point. The stiffness formulation not accounting for the latter is known as conventional stiffness formulation, which is obviously not complete and is valid only when: 1) the manipulator is in an unloaded quasistatic configuration and 2) the manipulator Jacobian matrix is constant throughout the workspace. The experimental system considered in this study is a Motoman SK 120 robot manipulator with a closed-chain mechanism. While the deflection of the manipulator end point under a range of external forces is provided by a high precision laser measurement system, a wrist force/torque sensor measures the external forces. Based on the experimental data and the enhanced stiffness model, the joint stiffness values are first identified. These stiffness values are then used to prove that conventional stiffness modeling is incomplete. Finally, they are employed to characterize stiffness properties of the robot manipulator. It has been found that although the component of the stiffness matrix differentiating the enhanced stiffness model from the conventional one is not always positive definite, the resulting stiffness matrix can still be positive definite. This follows that stability of the stiffness matrix is not influenced by this stiffness component. This study contributes to the previously reported work from the point of view of using the enhanced stiffness model for stiffness identification, verification and characterization, and of new experimental results proving that the conventional stiffness matrix is not complete and is valid under certain assumptions.

This paper presents a methodology for optimum dynamic balancing of planar parallel manipulators typified with a variable speed 2 DOF parallel manipulator articulated with revolute joints. The dynamic balancing is formulated as an optimisation problem such that a sum-squared values of bearing forces, driving torques, shaking moment, and the deviation of the angular momentum from its mean value are minimized throughout an operation range of the manipulator, provided that a set of balancing constraints consisting of the shaking force balancing conditions, the sizes of some inertial and geometric parameters are satisfied. Sets of optimisation results corresponding to various combinations of the elements of the objective function are evaluated in order to quantify their influence on the resulting bearing forces, the driving torques, shaking moment and force. The results prove that the proposed optimisation approach can be used to minimize any desired combination of the forces, moments, and torques involved in any parallel mechanism by choosing a suitable set of weighting factors. The method is systematic, versatile and easy to implement for the optimum balancing of the parallel manipulator and more general parallel manipulators.

This paper deals with optimum force balancing of a planar parallel manipulator, articulated with revolute joints, by properly distributing link masses, and connecting only one spring between its two coupler links. After conducting the static force analysis of the mechanism, the force balancing is formulated as an optimisation problem such that a sum-squared values of bearing forces is minimized throughout an operation range of the manipulator, provided that a set of balancing constraints consisting of balancing conditions, the sizes of some inertial and geometric parameters are satisfied. Optimisation results indicate that the proposed optimisation approach is systematic, versatile and easy to implement for the optimum balancing of the parallel manipulator and other more general parallel manipulators. This work contributes to previously published work from the point of view of being a step towards optimum design of parallel manipulators, which is currently lacking in the literature.

This paper aims (i) to introduce a new monolithic micromanipulation system for applications requiring micro/nano scale planar motion, and (ii) to model its stiffness consisting of the inherent stiffness of its joints, and the artificial stiffness due to its joint space position controller in order to obtain a decoupled compliant motion for the manipulator end point while a Cartesian force vector is acting upon it. The micromanipulation system is an in-parallel actuated planar manipulator based on five single DOF flexure joints connecting five supposedly rigid links to each other. Numerical results provided show that there exist practical operation ranges of the manipulator yielding both a suitable set of joint serve gains as well as a diagonal Cartesian stiffness matrix. The stiffness model can be used to predict the reaction forces arising from part misalignment and the task forces during the execution of micro tasks, such as micromanufacturing and microassembly. The determination of the forces is also useful for many applications such as designing micro fixtures and micro end effectors sustainable to task forces.

In this paper, we present the results and implications of our experimental study into the parameter identification and the position error modelling of a Motoman SK 120 robot manipulator for kinematic calibration. The true values of the parameters and the coefficients of the error model are estimated, in the least-squares sense, from the position data of 85 identification configurations of the manipulator measured by a high precision laser tracking system. The proposed error model is utilised to calculate the expected position errors for an exemplary Cartesian space trajectory. These errors are then corrected using a first order approximation of the inverse kinematic model. The results prove that the established model is accurate enough to represent position error of the manipulator without needing further experimental position data. This work contributes to previously published work from the point of view of being a simple and systematic approach to the self-calibration of robotics systems with minimum experimental data.

Current methods for singularity avoidance are analysed through study of the Jacobian minors. It is demonstrated that semi-singular positions, often defined as positions where dexterity decreases, occur as one minor becomes zero and that the only truly, uncontrollable, singular regions occur when all minors are zero. Existing singularity avoidance methods are analysed with attention to the way they deal with semi-singular regions. An 8-Degree Of Freedom (8-DOF) redundant autonomous articulated robot is used to demonstrate the effectiveness of the studied methods. Particular attention is made to the inherent limitations caused by a desire to maintain the aspect (sometimes referred to as configuration) in which the robot is operating. The use of the minors in manipulator analysis is shown to be useful in clarifying what truly occurs when dexterity is lost.

This paper presents the analysis and characterisation of force controlled robotic drilling. We demonstrate that a robot manipulator can perform drilling if enough contact thrust-force is provided between a workpiece and drill, and is controlled properly. It is shown that the key parameters for robotic drilling are the drill rotational speed and thrust force. We believe that this implementation of a force control strategy on a robot manipulator for robotic drilling is unique; nobody has previously reported on the end point force control of a robot manipulator using a force/torque sensor for a drilling operation.>

An experimental comparison of model-based joint space position control (JSPC) and Cartesian space position control (CSPC) strategies for the same manipulator, trajectory, sample rate, and dynamic model is presented. It is shown that the achievable tracking performance (in terms of the peak tracking error) and disturbance rejection capability of JSPC was experimentally better than that of CSPC for the same sample rate. High feedback gains for CSPC were found to be unachievable, which the authors suggest is due to the incompatibility between actuation and control space. The effect of varying the trajectory velocity, and of using a diagonal or full mass matrix in the control torque computation on the performance of the both strategies is also presented.

Describes the development and experimental verification of a mathematical model for a force control system consisting of a PUMA 560 manipulator, force sensor, and environment. The main contribution is an argument that explicit dynamic models of manipulation systems used for force control are of little relevance or use. Identification techniques are used to model the system as a black box, measuring only an input/output relationship. The explicit dynamics of the mechanical, hardware, and software elements of the manipulator are neglected; they are considered as parts of the measured input/output relationship. P+D loops are closed around each joint of the manipulator before identification to reduce the uncertainties, to overcome nonlinearities, and thus to linearize the system. Close correspondence between the experimental and the simulated Bode plots for frequencies below 30 Hz indicates that the model developed accurate enough to be used to analyze and design a force control strategy for hard-on-hard contact applications, e.g., robotic drilling.