Validation of an Extensible Rod Model for Soft continuum Manipulators

This paper introduces and validates a real-time dynamic predictive model based on a neural network approach for soft continuum manipulators. The presented model provides a real-time prediction framework using neural-network-based strategies and continuum mechanics principles. A time-space integration scheme is employed to discretize the continuous dynamics and decouple the dynamic equations for translation and rotation for each node of a soft continuum manipulator. Then the resulting architecture is used to develop distributed prediction algorithms using recurrent neural networks. The proposed RNN-based parallel predictive scheme does not rely on computationally intensive algorithms; therefore, it is useful in real-time applications. Furthermore, simulations are shown to illustrate the approach performance on soft continuum elastica, and the approach is also validated through an experiment on a magnetically-actuated soft continuum manipulator. The results demonstrate that the presented model can outperform classical modeling approaches such as the Cosserat rod model while also shows possibilities for being used in practice.

Planar soft space robotic manipulators: Dynamic modeling and control

Position regulation in Cartesian space of a class of inextensible soft continuum manipulators with pneumatic actuation

Continuum manipulators are continuously bending robots with unlimited number of kinematic degrees of freedom. Most existing continuum manipulators have a central strut made of a single elastic material, and multiple cables placed around the strut are employed to actuate the manipulator. The kinematics for such robots has been extensively studied by assuming the manipulator has a circular shape. In this paper, we aim to investigate the kinematic and static modeling for novel soft continuum manipulators fabricated by multi-material 3D printing with heterogeneous soft materials. We model cylindrical shape manipulators consisting of three sections with three different materials, and they are actuated by three independent cables placed symmetrically. By pulling the cables with different displacements, the manipulators can be bent in three-dimensional space. As our initial study, we employ a single cable for all prototypes. Experimental results are compared with the simulation results to validate the proposed modeling method.

Due to the requirements of industrial automation, soft manipulators are increasingly used in machinery manufacturing, metallurgy, and other fields. Typically, a manipulator is only suited to handle objects in ideal dry conditions, which limits the applications of these actuators. To solve the above-mentioned shortcomings in traditional grippers, this paper presents a friction-enhanced soft manipulator that has good flexibility and high interactivity and safety and is also equipped with a bionic nanofiber array film to provide stronger friction under slippery conditions. A polydimethylsiloxane (PDMS) nanofiber array film for increasing the friction of the soft manipulator was fabricated. A suitable manufacturing method for preparing the nanofiber array film was presented. The contact angle of the prepared nanofiber array film was measured. The experimental results showed that the soft robot manipulator performs extremely well under slippery conditions.

PurposeThe current methods for inspecting tall or deep structures such as towers, chimneys, silos, and wells suffer from certain constraints. Manual and assisted inspection methods including humans, drones, wall climbing robots, and others are either costly, have a limited operation time, or affected by field conditions, such as temperature and radiation. This study aims to overcome the presented challenges through a teleoperated soft continuum manipulator capable of inspecting tall or deep structures with high resolution, an unlimited operation time and the ability to use different arms of the manipulator for different environments and structure sizes.Design/methodology/approachThe teleoperated manipulator uses one rotary and two tendon actuators to reach and inspect the interior of a tall (or deep) structure. A sliding part along the manipulator’s body (arm constrainer and tendon router) induces a variable-length bending segment, allowing an inspection camera to be placed at different distances from the desired location.FindingsThe experiments confirmed the manipulator’s ability to inspect different locations in the structure’s interior. The manipulator also demonstrated a submillimeter motion resolution vertically and a 2.5 mm per step horizontally. The inspection time of the full structure was 48.53 min in the step-by-step mode and was calculated to be 4.23 min in the continuous mode.Originality/valueThe presented manipulator offers several design novelties: the arm’s thin-wide cross-section, the variable-length bending segment in a fixed-length body, the external rolling tendon routing and the ability to easily replace the arm with another of different material or dimensions to suite different structures and environments.

Mitigating fatigue damage and improving grasping performance are the two main challenging tasks of applying the soft manipulator into industrial production. In this paper, the grasping position optimization-based control strategy is proposed for the soft manipulator and the corresponding characteristics are studied theoretically and experimentally. Specifically, based on the simulation, the resultant stress of step-function-type channels at the same pressure condition that was smallest compared with those of sine-function- and ramp-function-type channels, hence, a pneumatic network with step-function-type channels was selected for the proposed soft manipulator. Furthermore, in order to improve the grasping performance, the kinematics, mechanical, and grasping modeling for the soft manipulator were established, and a control strategy considering the genetic algorithm is introduced to detect the optimal position of the soft manipulator. The corresponding fabrication process and experiments were conducted to cross verify the results of the modeling and the control strategy. It is demonstrated that the internal pressure of the soft manipulator was reduced by 13.05% at the optimal position, which effectively helped mitigate the fatigue damage of the soft manipulator and prolonged the lifespan.

Soft Continuum manipulators are increasingly popular because of their ability to interact safely with humans, maneuver around obstacles and enable cost-effective operation. In this paper, we investigate a unique manipulator composed of two asymmetric fiber reinforced pneumatic building blocks, one capable of bending and the other axially rotating. The combination of these building blocks can yield spatial motion including helical deformation pattern. While this design architecture is beneficial for whole arm manipulation and grasping, the asymmetric combination introduces structural coupling between the two modes rendering an analytical model hard to formulate. In this paper, we propose a Cosserat rod model to capture the deformation of the manipulator whose material properties and actuation parameters are estimated through extensive experiments. Once the model parameters are determined, the Cosserat model can be used to estimate deformation profile even in the presence of external loads. Such a framework is general and can be applied to obtain the forward and inverse kinematics of any continuum manipulator.

Soft robotics offer biocompatibility, dexterity, and safe tissue interaction in surgery, providing potential alternatives to conventional tools such as colonoscopes. However, their nonlinear behaviour demands closed-loop control with structure-compatible feedback. This work presents a scalable 3D shape-sensing method based on Electrical Impedance Tomography (EIT), unifying actuation and sensing of a hydraulically actuated soft robot within a neural network framework. A soft continuum manipulator (14.6 mm in diameter) with saline-pressurised chambers and embedded kirigami-inspired FPCs was evaluated in free motion and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ex vivo</i> porcine colon trials. A multilayer perceptron (MLP) predicted the full 3D shape, achieving tip RMSEs of 0.46, 0.20, and 0.40 mm (x, y, z) in free motion, and 1.96, 0.86, and 0.89 mm in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ex vivo</i>. This paper marks the first <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ex vivo</i> validation of EIT-based shape sensing in soft endoscopy and demonstrating its potential for closed-loop surgical control.

In this paper, the results of several experiments made on the control of oscillations of a single module of the I-Support manipulator are presented. The I-Support is a soft continuum robotic manipulator composed of several similar modules, designed and built for assisting disabled users during a showering task. For these experiments, a single module is pneumatically actuated by three sets of bellow-like actuators, that allow controlled bending in any direction and also controlled extension. The actuators are made of latex and braided polyester components that, when pressurized, make up the load-carrying structure of the module. As motion control of even a single module is a complex non-linear problem, a stepwise approach was followed where several signal based control techniques were tested for feasibility. These techniques focus on the oscillation control itself, meaning that it is assumed that the inverse kinematics problem—the definition of the input signals that will allow the robot to reach a specified equilibrium position—is dealt with elsewhere. Results show that pre-filtering the input commands significantly reduces overshoot and settling time for a task in three-dimensional space. Also, closed-loop control based on feeding back the error from the equilibrium position showed promising results but has for now only been applied to one-dimensional problems.KeywordsFlexible robotsSoft robotsVibration controlFlexible structures

Unlike traditional rigid-linked robots, soft robotic manipulators can bend into a wide variety of complex shapes due to control inputs and gravitational loading. This paper presents a new approach for modeling the dynamics of soft robotic manipulators that incorporates the effect of material nonlinearities and distributed and payload weight and is geometrically exact for the large curvature, shear, torsion and extension that often occur in these manipulators. The model is based on the general Cosserat theory of rods and a fiber reinforced model of air muscle actuators. The model is validated experimentally on the OctArm V manipulator, showing less that 5% average error for a wide range of actuation pressures and base orientations as compared to almost 50% average error for the constant curvature model previously used by researchers.

With the superior ductility and flexibility brought by compliant bodies, soft manipulators provide a nondestructive manner to grasp delicate objects, which has been developing gradually as a rising focus of soft robots. However, the unexpected phenomenon caused by environmental effects, leading to high internal nonlinearity and unpredictable deformation, makes it challenging to design, model, and control soft manipulators. In this paper, we designed a soft pneumatically actuated manipulator consisting of four soft actuators, as well as a flange, and investigated the influence of structural parameters on the output characteristics of the manipulator through finite element analysis (FEA). To enhance the bending deformation of the soft actuator, annular rings were employed on the soft actuator. A mathematical model for the bending deformation of air cavities was established to explore the relationship between the driving pressure and the bending angle based on the Yeoh strain energy function. Moreover, an end-output force model was established to depict the variation of the force output with the bending angle of the soft actuator, which was then experimentally validated by adopting the manufactured manipulator. The soft actuator studied in this paper can bend from 0° to 110° under an applied pressure of 0–60 kPa, and the maximum grasping load of the soft manipulator is 5.8 N. Finally, practical tests were conducted to assess the adaptability of the soft manipulator when grasping delicate fruits, such as apples, pears, tomatoes, and mangoes, demonstrating its broad application prospects in nondestructive fruit harvesting.

Laparoscopic surgeons perform precise and time consuming procedures while holding awkward poses in their upper body and arms. There is an ongoing effort to produce robotic tools for laparoscopic surgery that will simplify these tasks and reduce risk of errors to help both the surgeon and the patient. STIFF-FLOP is an ongoing EU FP7 project focusing on this by creating a stiffness controllable soft robotic manipulator. This paper reports on a study to test the soft manipulator's learnability and the effort associated with its use. The tests involved a limited prototype of the manipulator with a custom built test rig and EMG acquisition system. Task times and video recordings along with EMG waveforms from the forearm muscles of participants (n=25) were measured for objective assessment. A questionnaire was also provided to the participants for subjective assessment. The data shows that in average EMG levels were 25.9% less in RMS when using the STIFF-FLOP arm than when conventional laparoscopic tools were used. In terms of learnability, from the first to the second attempt on the STIFF-FLOP manipulator, elapsed time was reduced by an average of 32.1%. Further details and analysis of the EMG signals as well as time and questionnaire results is presented in the paper.

The technology of soft continuum robots represents an advance in the field of robotics to benefit a wide range of industries such as healthcare, manufacturing or environmental exploration. Soft continuum robots can be driven pneumatically by bellows as the soft continuum manipulator presented in this article. A driving torque model of the bellows considering hyperelastic material properties, friction and restoring torques is derived, whose purpose is suitability for model-based control design and subsequent trajectory generation. Hence, the driving torque model must be real-time capable. This is realized by an iterative algorithm calculating the bellows’ torque transmission by assuming a two-dimensional no-slip membrane contact. Nonlinear strain behaviours and hysteresis effects of the bellows are considered by the Ogden material model. The driving torque model’s performance is validated experimentally by measuring the external torques of the bellows.

Agriculture and horticulture depend heavily on human labor to perform tasks that are often dirty, hazardous, and highly repetitive. One reason for the lack of automation of these tasks is the absence of suitable robotic handling equipment. Rigid robotic manipulators are typically incapable of performing dexterous manipulation tasks such as harvesting apples as they lack the ability to adapt to objects of various shapes and sizes. Such robotic manipulators need a large number of sensors and actuators to overcome these challenges, making them overly complex and not very robust. Therefore, the development of robotic manipulators for dexterous manipulation tasks has begun to focus on morphological computation, in which at least some aspects of the control are outsourced to the body of the robot. Taking inspiration from grasping mechanisms in natural systems, the field of soft robotics attempts to address this problem by constructing robots from soft materials. Although soft robotics may be the key to realizing automation of dexterous manipulation tasks, the current commercially available soft robotic grippers are only capable of performing simple pick-and-place tasks with open-loop control. This limited capability is in large part due to a lack of techniques to endow these manipulators with a sense of self-movement and body position, known as proprioception. Proprioception is a simple problem for conventional robots with rigid members and discrete joints, as the body position can be easily reconstructed using the information from encoders in the robots’ joints. However, it is a highly challenging problem for soft robots with virtually infinite degrees of freedom and above all, no suitable off-the-shelf sensors…