Planar soft space robotic manipulators: Dynamic modeling and control

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.

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.

<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>

This paper presents the inverse kinematic analysis of a planar bio-inspired soft robot in a discrete task space using artificial intelligence (AI). The soft robot manipulator comprises a stack of hydraulically amplified dielectric elastomer actuators, which exhibit snap-through instability, resulting in a discrete robot task space. The model simulates the manipulator with a series of adjustable-length rods connected with revolute joints and satisfies the piecewise constant curvature (PCC) requirement for each robot segment. The discrete task space of the robot was estimated using the Monte Carlo method. The inverse kinematic analysis was carried out through genetic algorithm optimization with an embedded forward kinematic model to minimize the error for both the position and the orientation of the robot's end-effector. We analyze the fully controlled robot at each discrete segment, and we compare the results with the reduced complexity model obtained by grouping the actuator in sets of different sizes. The algorithm showed excellent results and can potentially be used in the analysis of similar soft manipulators with discrete task spaces.

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.

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.

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.

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.

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.

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…

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.

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 imitation of the functions of soft animals has always been the goal of soft robotic design. However, most of the current soft terrestrial robots just imitate the basic gaits and are difficult to perform in three dimensional space. In this work, we present an inchworm-inspired soft robot that integrates the locomotion and manipulation functions together. The soft robot is able to move in the vertical plane from one pole to another or work as a soft manipulator. The two functions can switch between each other naturally. Besides, the soft robot is unfettered by gravity, which greatly expands the applications of the soft robot. The deformation and load capacities of the soft components were tested, and to enhance the stiffness of the whole soft robot, the rigid-frame reinforcement was used. The performance of the soft robot shows great potential of actual applications, such as spatial maintenance and agricultural picking. Most importantly, the combination of the locomotion and manipulation functions provides a new idea for designing more applicable soft robots.

Soft robotics is a promising field and its application to space mechanisms could represent a breakthrough in space Technologies by enabling new operative scenarios (e.g. soft manipulators, capture systems). Dielectric Elastomers Actuators have been under deep study for a number of years and have shown several advantages that could be of key importance for space applications. Among such advantages the most notable are high conversion efficiency, distributed actuation, self-sensing capability, multi-degree-of-freedom design, light weight and low cost. The big potentialities of double cone actuators have
\nbeen proven in terms of good performances (i.e. stroke and force/torque), ease of manufacturing and durability. In this work the kinematic, dynamic and control design of a two-joint redundant robotic arm is presented. Two double cone actuators are assembled in series to form a two-link design. Each joint has two degrees of freedom (one rotational and one translational) for a total of four. The arm is designed to move in a 2-D environment (i.e. the horizontal plane) with 4 DoF, consequently having two degrees of redundancy. The redundancy is exploited in order to minimize the joint loads. The kinematic design with redundant Jacobian inversion is presented. The selected control algorithm is described along with
\nthe results of a number of dynamic simulations that have been executed for performance verification. Finally, an experimental setup is presented based on a flexible structure that counteracts gravity during testing in order to better emulate future zero-gravity applications.