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This paper aims to present a soft closed-chain modular gripper for robotic pick-and-place applications. The proposed biomimetic gripper design is inspired by the Fin Ray effect, derived from fish fins physiology. It is composed of three axisymmetric fingers, actuated with a single actuator. Each finger has a modular under-actuated closed-chain structure. The finger structure is compliant in contact normal direction, with stiff crossbeams reorienting to help the finger structure conform around objects.

Starting with the design and development of the proposed gripper, a consequent mathematical representation consisting of closed-chain forward and inverse kinematics is detailed. The proposed mathematical framework is validated through the finite element modeling simulations. Additionally, a set of experiments was conducted to compare the simulated and prototype finger trajectories, as well as to assess qualitative grasping ability.

Key Findings are the presented mathematical model for closed-loop chain mechanisms, as well as design and optimization guidelines to develop controlled closed-chain grippers.

The proposed methodology and mathematical model could be taken as a fundamental modular base block to explore similar distributed degrees of freedom (DOF) closed-chain manipulators and grippers. The enhanced kinematic model contributes to optimized dynamics and control of soft closed-chain grasping mechanisms.

The approach is aimed to improve the development of soft grippers that are required to grasp complex objects found in human–robot cooperation and collaborative robot (cobot) applications.

The proposed closed-chain mathematical framework is based on distributed DOFs instead of the conventional lumped joint approach. This is to better optimize and understand the kinematics of soft robotic mechanisms.

Soft robotics, regarded as a new research branch of robotics, has generated increasing interests in this decade and has demonstrated its outperformance in addressing safety issues when cooperating with human beings. However, there is still lack of accurate close-loop control because of the difficulty in acquiring feedback information and accurately modeling the system, especially in interactive environments. To this end, this paper aims to improve the controllability of the soft robot working in specific underwater environment. The system dynamics, which takes complicated hydrodynamics into account, is solved using Kane’s method. The dynamics-based adaptive visual servoing controller is proposed to realize accurate sensorimotor control.

This paper presents an image-based visual servoing control scheme for a cable-driven soft robot with a fixed camera observing the motions. The intrinsic and extrinsic parameters of the camera can be adapted online so that tedious camera calibration work can be eliminated. It is acknowledged that kinematics-based control can be only applied into tasks in the free space and has limitation in accelerating the motion speed of robot arms. That is, one must consider the unneglectable interaction effects generated from the environment and objectives when operating soft robots in such interactive control tasks. To extend the application of soft robots into underwater environment, the study models system dynamics considering complicated hydrodynamic effects. With the pre-knowledge of the external effects, the performance of the robot can be further improved by adding the compensation term into the controller.

The proposed controller has theoretically proved its convergence of image error, adaptive estimation error and the stability of the dynamical system based on Lyapunov’s analysis. The authors also validate the performance of the controller in positioning control task in an underwater environment. The controller shows its capacity of rapid convergence to and accurate tracking performance of a static image target in a physical experiment.

To the best of the authors’ knowledge, there is no such research before that has developed dynamics-based visual servoing controller which takes into account the environment interactions. This work can thus improve the control accuracy and enhance the applicability of soft robotics when operating in complicated environments.

The purpose of this paper is to review the latest developments, both in terms of products and manufacturing, of the Festo company.

This paper is a result of a visit made to Festo and also the Motek show in 2010.

Festo is developing new products which will not only enable new applications for automation, but also challenge the traditional approach of applying standard robots or gantries.

The paper provides an overview of the latest Festo developments highlighting their importance.

The purpose of this paper is to investigate the process of fused filament fabrication (FFF) of a compliant gripper (CG) using thermoplastic polyurethane (TPU) material. The paper studies the applicability of different CG designs and the efficiency of some design parameters.

After reviewing a number of different papers, two designs were selected for a number of exploratory experiments. Using design of experiments (DOE) techniques to identify important design parameters. Finally, the efficiency of the parts was investigated.

The research finds that a simpler design sacrifices some effectiveness in exchange for a remarkable decrease in production cost. Decreasing infill percentage of previous designs and 3D printing them, out of TPU, experimenting with different parameters yields functional products. Moreover, the paper identified some key parameters for further optimization attempts of such prototypes.

The cost of conducting FFF experiments for TPU increases dramatically with product size, number of parameters studied and the number of experiments. Therefore, all three of these factors had to be kept at a minimum. Further confirmatory experiments encouraged.

This paper addresses an identified need to investigate applications of FFF and TPU in manufacturing functional efficient flexible mechanisms, grippers specifically. While most research focused on designing for increased performance, some research lacks discussion on design philosophy, as well as manufacturing issues. As the needs for flexible grippers vary from high-performance grippers to lower performance grippers created for specific functions/conditions, some effectiveness can be sacrificed to reduce cost, reduce complexity and improve applicability in different robotic assemblies and environments.

This paper aims to illustrate the increasingly important role played by tactile sensing in robotics by considering three specific fields of application.

Following a short introduction, this paper first provides details of tactile sensing principles, technologies, products and research. The following sections consider tactile sensing applications in robotic surgery, collaborative robots and robotic grippers. Finally, brief conclusions are drawn.

Tactile sensors are the topic of an extensive and technologically diverse research effort, with sensing skins attracting particular attention. Many products are now available commercially. New generations of surgical robots are emerging which use tactile sensing to provide haptic feedback, thereby eliminating the surgeon’s total reliance on visual control. Many collaborative robots use tactile and proximity sensing as key safety mechanisms and some use sensing skins. Some skins can detect both human proximity and physical contact. Sensing skins that can be retrofitted have been developed. Commercial tactile sensors have been incorporated into robotic grippers, notably anthropomorphic types, and allow the handling of delicate objects and those with varying shapes and sizes. Tactile sensing uses will inevitably increase because of the ever-growing numbers of robots interacting with humans.

This study provides a detailed account of the growing use of tactile sensing in robotics in three key areas of application.

Soft robotics is currently a rapidly growing new field of robotics whereby the robots are fundamentally soft and elastically deformable. Fabrication of soft robots is currently challenging and highly time- and labor-intensive. Recent advancements in three-dimensional (3D) printing of soft materials and multi-materials have become the key to enable direct manufacturing of soft robots with sophisticated designs and functions. Hence, this paper aims to review the current 3D printing processes and materials for soft robotics applications, as well as the potentials of 3D printing technologies on 3D printed soft robotics.

The paper reviews the polymer 3D printing techniques and materials that have been used for the development of soft robotics. Current challenges to adopting 3D printing for soft robotics are also discussed. Next, the potentials of 3D printing technologies and the future outlooks of 3D printed soft robotics are presented.

This paper reviews five different 3D printing techniques and commonly used materials. The advantages and disadvantages of each technique for the soft robotic application are evaluated. The typical designs and geometries used by each technique are also summarized. There is an increasing trend of printing shape memory polymers, as well as multiple materials simultaneously using direct ink writing and material jetting techniques to produce robotics with varying stiffness values that range from intrinsically soft and highly compliant to rigid polymers. Although the recent work is done is still limited to experimentation and prototyping of 3D printed soft robotics, additive manufacturing could ultimately be used for the end-use and production of soft robotics.

The paper provides the current trend of how 3D printing techniques and materials are used particularly in the soft robotics application. The potentials of 3D printing technology on the soft robotic applications and the future outlooks of 3D printed soft robotics are also presented.

This paper aims to review the shape sensing techniques using large area flexible electronics (LAFE). Shape perception of humanoid robots using tactile data is mainly focused.

Research papers on different shape sensing methodologies of objects with large area, published in the past 15 years, are reviewed with emphasis on contact-based shape sensors. Fiber optics based shape sensing methodology is discussed for comparison purpose.

LAFE-based shape sensors of humanoid robots incorporating advanced computational data handling techniques such as neural networks and machine learning (ML) algorithms are observed to give results with best resolution in 3D shape reconstruction.

The literature review is limited to shape sensing application either two- or three-dimensional (3D) LAFE. Optical shape sensing is briefly discussed which is widely used for small area. Optical scanners provide the best 3D shape reconstruction in the noncontact-based shape sensing; here this paper focuses only on contact-based shape sensing.

Contact-based shape sensing using polymer nanocomposites is a very economical solution as compared to optical 3D scanners. Although optical 3D scanners can provide a high resolution and fast scan of the 3D shape of the object, they require line of sight and complex image reconstruction algorithms. Using LAFE larger objects can be scanned with ML and basic electronic circuitory, which reduces the price hugely.

LAFE can be used as a wearable sensor to monitor critical biological parameters. They can be used to detect shape of large body parts and aid in designing prosthetic devices. Tactile sensing in humanoid robots is accomplished by electronic skin of the robot which is a prime example of human–machine interface at workplace.

This paper reviews a unique feature of LAFE in shape sensing of large area objects. It provides insights from mechanical, electrical, hardware and software perspective in the sensor design. The most suitable approach for large object shape sensing using LAFE is also suggested.

This paper aims to imitate a cownose ray to develop a fish robot with paired flexible multi-fin-ray oscillating pectoral fins (OPFs) and control it to accomplish vivid stable 3-D motions using central pattern generators (CPGs) and fuzzy algorithm.

The cownose ray’s asymmetric sine-like oscillations were analyzed. Then a cownose-ray-like fish robot named Robo-ray was developed, which has paired flexible multi-fin-ray OPFs to actively control the fin shape and two tail fins to control the depth. To solve the problem of coordinated control for multi-degree-of-freedom Robo-ray, CPGs were adopted. An improved phase oscillator as a CPG unit with controlled amplitude, phase lag, smooth frequency transition and asymmetric oscillation characteristic was established. Furthermore, the CPG-fuzzy algorithm was developed for vivid stable 3-D motions. The open-loop speed control, the closed-loop control of depth and yaw were established.

The kinematic comparisons indicate that Robo-ray imitates the cownose ray realistically. The experimental results of closed-loop are obtained that the depth error of Robo-ray is less than ±100 mm and the course error is less than ±3°. Furthermore, the comprehensive experiments demonstrate that Robo-ray has high mobility, stability and robustness.

This research makes the fish robot with OPF propulsion closer to practical applications in complex underwater environment, for instance, ocean explorations, water quality monitoring and stealth military reconnaissance. In addition, Robo-ray can be taken as a scientific tool for better understanding of the hydrodynamics of OPF batoid.