Soft Robotic Arm Research Articles

Simplified dynamical model and experimental verification of an underwater hydraulic soft robotic arm

Inherent compliance equips soft robotic arms with such advantages as incomparable flexibility, good adaptability, and safe interaction with the environment, etc. However, the strong nonlinearity also brings challenges to predict their dynamic behaviors. This work presents a simplified dynamic model of an underwater soft robotic arm which has three fiber-reinforced hydraulic chambers distributed symmetrically in each section. By controlling the pressures in the chambers, the soft robotic arm can perform complex spatial motion with multiple degrees of freedom. The model is based on Lagrangian method and piecewise constant curvature hypothesis, and considers the nonlinear viscoelasticity of soft material. The model accuracy is verified by the experiments of a two-section soft robotic arm with different actuation modes. The effects of geometrical features on dynamic response are also investigated through model-based simulation and test verification, which can provide guidance to parameter optimization. The proposed dynamic model can be extended to multiple sections and contribute to behavior analysis, performance prediction, and motion control of the soft robotic arm.

Toward the Development of Large-Scale Inflatable Robotic Arms Using Hot Air Welding.

The manufacturing method of soft pneumatic robots affects their ability to maintain their impermeability when pressurized. Pressurizing them beyond their limits results in leaks or ruptures of the structure. Increasing their size simultaneously increases the tension forces within their structure and reduces their ability to withstand the pressures necessary for them to operate. This article introduces the use of hot air welding to manufacture three-dimensional inflatable elements containing only lap seals which can sustain larger tension forces than the fin seals used in most other inflatable robotic arms. This manufacturing technique is then used to form inflatable joints with 2-degrees of freedom (DOFs), which can be assembled to form 6-DOFs robotic arms. A dual-arm inflatable robot was built using two arms each with a length of 85 cm, was capable of lifting payloads up to 3 kg, had a large range of motion, and was able to lift misaligned boxes using its two arms relying only on friction force by pushing on both sides of the box. The arm concept was then scaled to form a robotic arm with a length of nearly 5 m, which was able to pickup and place a basketball in a basketball hoop from the free-throw line several meters away. The present work advances the state of the art in building large-scale soft robotic arms.

Design, Implementation, and Kinematics of a Twisting Robot Continuum Arm Inspired by Human Forearm Movements

In this article, a soft robot arm that has the ability to twist in two directions is designed. This continuum arm is inspired by the twisting movements of the human upper limb. In this novel continuum arm, two contractor pneumatic muscle actuators (PMA) are used in parallel, and a self-bending contraction actuator (SBCA) is laid between them to establish the twisting movement. The proposed soft robot arm has additional features, such as the ability to contract and bend in multiple directions. The kinematics for the proposed arm is presented to describe the position of the distal end centre according to the dimensions and positions of the actuators and the bending angle of the SBCA in different pressurized conditions. Then, the rotation behaviour is controlled by a high precision controller system.

A Static Modeling Approach for Thin-Walled Soft Robotic Arms Considering Geometric and Material Nonlinearity

The current design based on air chambers makes thin wall a typical feature of soft robotic arms. Considering this characteristic, a new static modeling method that integrates the principle of virtual work and a spring-fluid equivalent modeling idea is proposed in this work. The method is able to consider both geometric and material nonlinearity of the soft robotic arm. A general physical model of the thin-walled soft robotic arm and the static modeling process are presented. Then, an experimental prototype of the thin-walled soft robotic arm is fabricated and the experimental verification of the proposed method is carried out. The comparisons between the theoretical prediction and experimental results under different load conditions illustrate that the proposed static modeling method can be used to describe the static deformation of soft robotic arms with high accuracy. The proposed static modeling method provides a new way to model the soft robotic arm and has guiding significance for the design of soft robotic arms.

Dynamic Finite Element Modeling and Simulation of Soft Robots

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.

Sim-to-Real for Soft Robots Using Differentiable FEM: Recipes for Meshing, Damping, and Actuation

An accurate, physically-based, and differentiable model of soft robots can unlock downstream applications in optimal control. The Finite Element Method (FEM) is an expressive approach for modeling highly deformable structures such as dynamic, elastomeric soft robots. In this paper, we compare virtual robot models simulated using differentiable FEM with measurements from their physical counterparts. In particular, we examine several soft structures with different morphologies: a clamped soft beam under external force, a pneumatically actuated soft robotic arm, and a soft robotic fish tail. We benchmark and analyze different meshing resolutions and elements (tetrahedra and hexahedra), numerical damping, and the efficacy of differentiability for parameter calibration using a simulator based on the fast Differentiable Projective Dynamics (DiffPD). We also advance FEM modeling in application to soft robotics by proposing a predictive model for pneumatic soft robotic actuation. Through our recipes and case studies, we provide strategies and algorithms for matching real-world physics in simulation, making FEM useful for soft robots.

Dynamic Control of Soft Robotic Arm: A Simulation Study

In this article, the control problem of one segment pneumatically actuated soft robotic arm is investigated in detail. To date, extensive prior work has been done in soft robotics kinematics and dynamics modeling. Proper controller designs can complement the modeling work since they are able to compensate the effects that have not been considered in the modeling, such as the model uncertainties, system parameter identification error, hysteresis, external forces, disturbances, etc. In this letter, we explored different control approaches (kinematic control, PD+feedback linearization, passivity control, adaptive passivity control) and summarized the advantages and disadvantages of each controller. We further investigated the robot control problem in the practical scenarios when the sensor noise exists, actuator velocity measurement is not available, the hysteresis effect is non-neglectable, as well as the existence of external force. Our simulation results indicated that the adaptive passivity control with sigma modification terms, along with a high-gain observer presents a better performance in comparison with other approaches. Although this paper mainly presented the simulation results of various controllers, the work here will pave the way for practical implementation of soft robot control.

Redundancy and overactuation in cephalopod-inspired soft robot arms

Current soft robotic arms commonly follow traditional—i.e. hard—robot design conventions. Omnidirectional soft arms most commonly consist of segments that contain three parallel longitudinal actuators, or actuator groups, of which one or two are activated to induce bending. This design uses the minimum number of actuators required for omnidirectional bending, which is consistent with traditional robot design but unnecessarily constrains the soft arm design space. The cephalopods that frequently inspire soft robot arms have tens of bundles of longitudinal muscle fibers, and these bundles are distributed around the limb circumference rather than grouped. This article analyzes fluid-driven soft arm architectures with up to 12 actuators, which mimics the redundant and distributed nature of cephalopod arms and tentacles, in order to investigate the performance implications of an arm morphology closer to nature. Overactuation (i.e. activating more than two actuators) was considered, which is possible because soft robots—unlike traditional robots—can tolerate misaligned or partially opposed actuation without jamming. A previously-developed generalizable model was used to simulate design performance, and a subset of the examined architectures were constructed and tested. Many-actuator soft arms achieve high strokes under equivalent load and equivalent actuation pressures, without sacrificing no-load reach. These arms are also able to achieve quasi-omnidirectionality, as well as to execute near constant-curvature turns using a simple actuation pattern and a single pressure signal. The introduced framework also enables non-circular cross sections that are not possible with minimalist arm designs, allowing the load capacity and reach to be tuned in multiple directions. Several elliptical cross section arms were analyzed to explore the potential of non-circular cross sections. Overactuated, many-actuator arms significantly expand the design space of soft arms, improving performance in some cases and introducing options to tailor behavior that are infeasible in structurally minimal arms.

Redundancy and overactuation in cephalopod-inspired soft robot arms.

Current soft robotic arms commonly follow traditional - i.e., hard - robot design conventions. Omnidirectional soft arms most commonly consist of segments that contain three parallel longitudinal actuators, or actuator groups, of which one or two are activated to induce bending. This design uses the minimum number of actuators required for omnidirectional bending, which is consistent with traditional robot design but unnecessarily constrains the soft arm design space. The cephalopods that frequently inspire soft robot arms have tens of bundles of longitudinal muscle fibers, and these bundles are distributed around the limb circumference rather than grouped. This article analyzes fluid-driven soft arm architectures with up to 12 actuators, which mimic the redundant and distributed nature of cephalopod arms and tentacles. Over-constraints (activating more than two actuators) were considered, which are possible because soft robots - unlike traditional robots - can tolerate conflicting constraints without jamming. A previously-developed generalizable model was used to simulate design performance, and a subset of the examined architectures were constructed and tested. Many-actuator soft arms achieved high strokes under equivalent load without sacrificing no-load reach and were able to execute near constant-curvature turns with a simple actuation pattern. The framework introduced here also enables cross section variations that are not possible with minimalist designs.

Elephant trunk shaped power soft robotic arm

Elephant trunk shaped power soft robotic arm

Design and Control of an Inflatable Spherical Robotic Arm for Pick and Place Applications

We present an inflatable soft robotic arm made of fabric that leverages state-of-the-art manufacturing techniques, leading to a robust and reliable manipulator. Three bellow-type actuators are used to control two rotational degrees of freedom, as well as the joint stiffness that is coupled to a longitudinal elongation of the movable link used to grasp objects. The design is motivated by a safety analysis based on first principles. It shows that the interaction forces during an unexpected collision are primarily caused by the attached payload mass, but can be reduced by a lightweight design of the robot arm. A control allocation strategy is employed that simplifies the modeling and control of the robot arm and we show that a particular property of the allocation strategy ensures equal usage of the actuators and valves. The modeling and control approach systematically incorporates the effect of changing joint stiffness and the presence of a payload mass. An investigation of the valve flow capacity reveals that a proper timescale separation between the pressure and arm dynamics is only given for sufficient flow capacity. Otherwise, the applied cascaded control approach can introduce oscillatory behavior, degrading the overall control performance. A closed form feed forward strategy is derived that compensates errors induced by the longitudinal elongation of the movable link and allows the realization of different object manipulation applications. In one of the applications, the robot arm hands an object over to a human, emphasizing the safety aspect of the soft robotic system. Thereby, the intrinsic compliance of the robot arm is leveraged to detect the time when the robot should release the object.

Kinematic modeling and control of a novel pneumatic soft robotic arm

A novel soft robotic arm (SRA) composed of two soft extensible arms (SEAs) and a soft bendable joint (SBJ) for space capture systems is presented in this paper. A diamond origami pattern was applied in the design of the SEAs, and large deformations of the SEAs in positive pressure were simulated using the nonlinear finite element method. A kinematic model of the SRA using the Denavit–Hartenberg method based on the assumption of constant curvatures was proposed. A closed-loop model-free control system based on a PID controller was developed using real-time data from a vision sensor system. The kinematic model and closed-loop model-free control system are experimentally evaluated on an SRA prototype by four experiments. The experimental results demonstrate that the derived kinematic model can finely describe the movement of the SRA and that the closed-loop control system can control the SRA to reach the desired destination or trajectory within an acceptable error and performs well in long-term repeated operations.

Elastica: A Compliant Mechanics Environment for Soft Robotic Control

Soft robots are notoriously hard to control. This is partly due to the scarcity of models and simulators able to capture their complex continuum mechanics, resulting in a lack of control methodologies that take full advantage of body compliance. Currently available methods are either too computational demanding or overly simplistic in their physical assumptions, leading to a paucity of available simulation resources for developing such control schemes. To address this, we introduce Elastica, an open-source simulation environment modeling the dynamics of soft, slender rods that can bend, twist, shear, and stretch. We couple Elastica with five state-of-the-art reinforcement learning (RL) algorithms (TRPO, PPO, DDPG, TD3, and SAC). We successfully demonstrate distributed, dynamic control of a soft robotic arm in four scenarios with both large action spaces, where RL learning is difficult, and small action spaces, where the RL actor must learn to interact with its environment. Training converges in 10 million policy evaluations with near real-time evaluation of learned policies.

A Vision-Based Sensing Approach for a Spherical Soft Robotic Arm.

Sensory feedback is essential for the control of soft robotic systems and to enable deployment in a variety of different tasks. Proprioception refers to sensing the robot’s own state and is of crucial importance in order to deploy soft robotic systems outside of laboratory environments, i.e. where no external sensing, such as motion capture systems, is available. A vision-based sensing approach for a soft robotic arm made from fabric is presented, leveraging the high-resolution sensory feedback provided by cameras. No mechanical interaction between the sensor and the soft structure is required and consequently the compliance of the soft system is preserved. The integration of a camera into an inflatable, fabric-based bellow actuator is discussed. Three actuators, each featuring an integrated camera, are used to control the spherical robotic arm and simultaneously provide sensory feedback of the two rotational degrees of freedom. A convolutional neural network architecture predicts the two angles describing the robot’s orientation from the camera images. Ground truth data is provided by a motion capture system during the training phase of the supervised learning approach and its evaluation thereafter. The camera-based sensing approach is able to provide estimates of the orientation in real-time with an accuracy of about one degree. The reliability of the sensing approach is demonstrated by using the sensory feedback to control the orientation of the robotic arm in closed-loop.

Harnessing the Multistability of Kresling Origami for Reconfigurable Articulation in Soft Robotic Arms.

This study examines a biology-inspired approach of using reconfigurable articulation to reduce the control requirement for soft robotic arms. We construct a robotic arm by assembling Kresling origami modules that exhibit predictable bistability. By switching between their two stable states, these origami modules can behave either like a flexible joint with low bending stiffness or like a stiff link with high stiffness, without requiring any continuous power supply. In this way, the robotic arm can exhibit pseudo-linkage kinematics with lower control requirements and improved motion accuracy. A unique advantage of using origami as the robotic arm skeleton is that its bending stiffness ratio between stable states is directly related to the underlying Kresling design. Therefore, we conduct extensive parametric analyses and experimental validations to identify the optimized Kresling pattern for articulation. The results indicate that a higher angle ratio, a smaller resting length at contracted stable state, and a large number of polygon sides can offer more significant and robust bending stiffness tuning. Based on this insight, we construct a proof-of-concept, tendon-driven robotic arm consisting of three modules and show that it can exhibit the desired reconfigurable articulation behavior. Moreover, the deformations of this manipulator are consistent with kinematic model predictions, which validate the possibility of using simple controllers for such compliant robotic systems.

Model-Based Control and External Load Estimation of an Extensible Soft Robotic Arm.

Soft robotics has widely been known for its compliant characteristics when dealing with contraction or manipulation. These soft behavior patterns provide safe and adaptive interactions, greatly relieving the complexity of active control policies. However, another promising aspect of soft robotics, which is to achieve useful information from compliant behavior, is not widely studied. This characteristic could help to reduce the dependence of sensors, gain a better knowledge of the environment, and enrich high-level control strategies. In this paper, we have developed a state-change model of a soft robotic arm, and we demonstrate how compliant behavior could be used to estimate external load based on this model. Moreover, we propose an improved version of the estimation procedure, further reducing the estimation error by compensating the influcence of pressure deadzone. Experiments of both methods are compared, displaying the potential effectiveness of applying these methods.

Optimal Structure and Size of Multi-segment Soft Robotic Arms with Finite Element Method

Pneumatic actuate of multi-segment soft robotic arm is a significant structure and has extensive applications. However, the study of the optimal structure and size of multi-segment soft robotic arm has not been achieved. In this study, the finite element method is used to optimized the structure and size of soft robotic arm. We report that the two-segment structure of soft robotic arm has better performance for the general manipulator operation task through evaluating bending angles with different structures and parameters. The optimal ratio of the total length of non-cavity section to the total length of the soft robotic arm with two-segment is 0.21. And soft robotic arm performs better when the length of the fixed first section, the linkage section between two cavity sections and the end section are equal. Two cavities in each segment has more advantages in tasks of plane bending, while three cavities structure has better adaptability when the task need bend in the space. These results in this study provide a reference and simplify the process for the structure and size design of the multi-segment soft robotic arm in the future.

Efficient Path Planning of Soft Robotic Arms in the Presence of Obstacles

Efficient Path Planning of Soft Robotic Arms in the Presence of Obstacles

Development of soft robotic arm for an avatar robot

Development of soft robotic arm for an avatar robot

Development of a 7-DoF Power Soft Robot driven by Hydraulic Artificial Muscles

The mechanisms of the current robotics are completely different from the muscle driving mechanisms of humans or animals. The 7-DOF power soft robot arm driven by hydraulic artificial muscles developed in this study can potentially achieve the coexistence of strength and softness while having motion characteristics close to those of humans. This robot has two antagonistic joints on the shoulder, two asymmetrical antagonistic joints on the upper arm and the lower arm, and the wrist and elbow have rotational pull-wire drive joints, a total of 29 hydraulic artificial muscles.