Model-less feedback control for soft manipulators

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.

Planar soft space robotic manipulators: Dynamic modeling and control

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.

In this paper, the design and testing of a novel valve for the intuitive spatial control of soft or continuum manipulators are presented. The design of the valve is based on the style of a hydraulic flapper valve, but with simultaneous control of three pressure feed points, which can be used to drive three antagonistically arranged hydraulic actuators for positioning soft robots. The variable control orifices are arranged in a rotationally symmetric radial pattern to allow for an inline mounting configuration of the valve within the body of a manipulator. Positioning the valve ring at various 3D configurations results in different pressurizations of the actuators and corresponding spatial configurations of the manipulator. The design of the valve is suitable for miniaturization and use in applications with size constraints such as small soft manipulators and surgical robotics. Experimental validation showed that the performance of the valve can be reasonably modeled and can effectively drive an antagonistic arrangement of three actuators for soft manipulator control.

Compared with rigid robots, soft robots have better adaptability to the environment because of their pliability. However, due to the lower structural stiffness of the soft manipulator, the posture of the manipulator is usually decided by the weight and the external load under operating conditions. Therefore, it is necessary to conduct dynamics modeling and movement analysis of the soft manipulator. In this paper, a fabric reinforced soft manipulator driven by a water hydraulic system is firstly proposed, and the dynamics of both the soft manipulator and hydraulic system are considered. Specifically, a dynamic model of the soft manipulator is established based on an improved Newton–Euler iterative method, which comprehensively considers the influence of inertial force, elastic force, damping force, as well as combined bending and torsion moments. The dynamics of the water hydraulic system consider the effects of cylinder inertia, friction, and water response. Finally, the accuracy of the proposed dynamic model is verified by comparing the simulation results with the experimental data about the steady and dynamic characteristics of the soft manipulator under various conditions. The results show that the maximum sectional error is about 0.0245 m and that the maximum cumulative error is 0.042 m, which validate the effectiveness of the proposed model.

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.

Soft manipulators have desirable environmental compatibility because of their pliability. However, this pliability also brings challenges to modeling and control when considering contact or collision with the environment. In previous work, we established several mathematical models for describing fluidic soft manipulators under environmental effects and verified their accuracy. However, the controller design for a soft manipulator is still a significant challenge, especially under the conditions of environmental contact. In this paper, we build upon our previously established work by conducting feedforward compensation for a soft manipulator under contact constraints and designing a sliding mode controller based on an operational space dynamics model. Then, we combine the feedforward compensation model with the sliding mode controller to realize accurate position control of the soft manipulator. Finally, simulation and experimental results show that this controller can accurately and effectively control the position of the soft manipulator.

Soft manipulator is a kind of special manipulator that uses soft material or flexible structure to perform manipulation task under the specific drive mode inspired by the soft tissue. It is developing gradually as an important component of the soft robot. In this paper, the typical design cases of the soft manipulators as well as the related research teams are firstly investigated. The characteristics of different drive modes are compared and analyzed. Based on these investigations, the enabling technologies are systematically summarized in five aspects, such as kinematic and dynamic modeling, motion control, shape detection, dynamic tactile perception, and stiffening method. Currently, the research on soft manipulator has initially formed a technical system, although it is still in the primary stage. With the development of the soft manipulator, its overall technology maturity will be gradually improved. Currently, the applications of the soft manipulator lie mainly in the fields of the ground rescue, the underwater grabbing, the medical operation, the assist maintenance, the man–machine interaction, the space manipulation and so on. The application fields, such as origami soft manipulator, biomimetic soft microrobots, self‐healing soft robot, space soft manipulator and so on, emerge new opportunities and challenges for the soft manipulators.

Soft robots are concerned by researchers due to several characteristics, such as high adaptability in complex unstructured environments, safe interaction with environments, and a high degree of dexterity. The deformability and dexterity of the octopus arm are remarkable and interesting for the development of bioinspiration soft robots. In this study, we proposed a biomimetic flexible manipulator actuated by shape memory alloy (SMA) wires and its PI controller, and evaluated its performances with focused experiments. This study aims to find out the advantages of the developed manipulator actuated by SMA wires. We designed the bionic structure to achieve flexible bending in 3D space based on the analysis of the octopus muscle structure. Then we built the mathematical models that described the relationship between the bending angle and the driving parameters. Surprisingly, the soft movement capacity of the bionic manipulator was investigated at different heating voltages and PWM duty cycles by the PI controller based on the self-sensing resistance feedback. The soft manipulator was able to bend flexibly with the maximum bending angle of 60°. Compared to the traditional soft arm, the soft manipulator has higher accuracy, with the error of the deflection angle less than 5° and the errors of bending angles less than 2°.

Robotic manipulators for minimally invasive surgeries have traditionally been rigid, with a steerable end effector. While the rigidity of manipulators improve precision and controllability, it limits reachability and dexterity in constrained environments. Soft manipulators with controllable stiffness on the other hand, can be deployed in single port or natural orifice surgical applications to reach a wide range of areas inside the body, while being able to passively adapt to uncertain external forces, adapt the stiffness distribution to suit the kinematic and dynamic requirements of the task, and provide flexibility for configuration control. Here, we present the design of a snake-like laboratory made soft robot manipulator of 20 mm in average diameter, which can actuate, soften, or stiffen joints independently along the length of the manipulator by combining granular jamming with McKibben actuators. It presents a comprehensive study on the relative contributions of the granule size, material type, and membrane coupling on the range, profile, and variability of stiffness.

Dynamic control of soft robotic manipulators is a challenging field still in its nascent stages. Modeling is still a major hurdle due to its high dimensional nonlinear dynamic properties. Even if accurate models of these high dimensional nonlinear systems are available, the computational burden of the models or sensory requirements poses problems for robust and stable control. This letter addresses these two problems by using a data-driven model that uses only mechanical feedback for stable control of the soft robotic manipulator. Using a learning-based open loop dynamic controller, we investigate the self-stabilizing behavior that can be obtained from the complex dynamics of a soft manipulator. Experimental findings illustrate the advantage of using open-loop dynamic controllers for accurate self-stabilizing control of soft robotic manipulators without any sensory feedback.

Traditionally, any new development in soft robotics has to come first through many trial-and-error experiments. Many researchers tried to develop analytical models either to study certain phenomena in an already existed deigns or to use them to enhance soft robots performance. However, there is no general methodology that can be used to design any arbitrary soft robot from scratch. Such methodology should have the ability to test different operation scenarios for checking certain control approaches or certain types of sensors and actuators. This paper introduces a general tool for developing soft surgical manipulators, which is based on transient finite element analysis (FEA). To verify the feasibility of the proposed approach, experiments have been conducted on a fabricated soft manipulator. The test setup incorporates pressure sensors and vision tracking system to record the manipulator trajectory. Air pressure measurements are used as input to FEA for transient simulation. The experimental results demonstrate high level of agreement with FEA results and prove that the suggested approach is promising to be used in designing new soft surgical robots.

Soft fiber-reinforced actuators with fibers embedded in elastomeric structures are excellent candidates in the soft robotics, which are characterized by high flexibility and adaptability. However, few works focus on the dynamics of soft fiber-reinforced actuators owing to their nonlinear properties for large material deformation. In this article, based on Cosserat rod theory, a dynamic modeling method implicitly discretizing the time derivatives of a set of partial differential equations besides addressing a boundary-value problem of ordinary differential equation at each time step, is proposed to describe the real-time bending, twisting, and elongation deformation characteristics of the manipulator. In particular, this method accounts for a pressure-time-dependent dynamic modulus and real-time external loads. In addition, we utilize our proposed method that can realize real-time simulation of the nonlinear deformation of the manipulator with external loads to demonstrate this method’s application. Finally, both the finite element analysis and experiments are conducted to evaluate the accuracy of our method. Results show that this method can effectively predict the real-time position of the manipulator, and the maximum real-time error rate of tracking end tip is less than 4%.

This paper presents a robotic manipulation system capable of autonomously positioning a multi-segment soft fluidic elastomer robot in three dimensions. Specifically, we present an extremely soft robotic manipulator morphology that is composed entirely from low durometer elastomer, powered by pressurized air, and designed to be both modular and durable. To understand the deformation of a single arm segment, we develop and experimentally validate a static deformation model. Then, to kinematically model the multi-segment manipulator, we use a piece-wise constant curvature assumption consistent with more traditional continuum manipulators. In addition, we define a complete fabrication process for this new manipulator and use this process to make multiple functional prototypes. In order to power the robot’s spatial actuation, a high capacity fluidic drive cylinder array is implemented, providing continuously variable, closed-circuit gas delivery. Next, using real-time data from a vision system, we develop a processing and control algorithm that generates realizable kinematic curvature trajectories and controls the manipulator’s configuration along these trajectories. Lastly, we experimentally demonstrate new capabilities offered by this soft fluidic elastomer manipulation system such as entering and advancing through confined three-dimensional environments as well as conforming to goal shape-configurations within a sagittal plane under closed-loop control.

<p>Soft robots have become important members of the robot community with many potential applications owing to their unique flexibility and security embedded at the material level. An increasing number of researchers are interested in their designing, manufacturing, modeling, and control. However, the dynamic simulation of soft robots is difficult owing to their infinite degrees of freedom and nonlinear characteristics that are associated with soft materials and flexible geometric structures. In this study, a novel multi-flexible body dynamic modeling and simulation technique is introduced for soft robots. Various actuators for soft robots are modeled in a virtual environment, including soft cable-driven, spring actuation, and pneumatic driving. A pneumatic driving simulation was demonstrated by the bending modules with different materials. A cable-driven soft robot arm prototype and a cylindrical soft module actuated by shape memory alley springs inspired by an octopus were manufactured and used to validate the simulation model, and the experimental results demonstrated adequate accuracy. The proposed technique can be widely applied for the modeling and dynamic simulation of other soft robots, including hybrid actuated robots and rigid-flexible coupling robots. This study also provides a fundamental framework for simulating soft mobile robots and soft manipulators in contact with the environment.</p> <p> </p>