Compliant mechanisms are flexible structures that utilize elastic deformation to achieve their desired motions. Using this unique mode of actuation, the compliant mechanisms have two distinct advantages over traditional rigid machines: (1) They can create highly repeatable motions that are critical for many high precision applications. (2) Their high degrees-of-freedom motions have the potential to achieve mechanical functionalities that are beyond traditional machines, making them especially appealing for miniature robots that are currently limited to only having simple rigid-body-motions and gripping functionalities. Unfortunately, despite the potential of compliant mechanisms, there are still several key challenges that restrict them from realizing their full potential. To facilitate this discussion, we first divide the compliant mechanisms into two categories: (1) the stiffer flexural mechanisms that are ideal for high precision applications, and (2) the more compliant miniature soft robots that can reshape their geometries to achieve highly complex mechanical functionalities. The key limitation for existing flexural mechanisms is that their stiffness and dynamic properties cannot be optimized when they have multi-degrees-of-freedom. This limitation has severely crippled the performance of flexural mechanisms because their stiffness and dynamic properties dictate their workspace, transient responses and capabilities to reject disturbances. On the other hand, miniature soft robots that have overall dimensions smaller than 1 cm, are unable to achieve their full potential because existing works do not have a systematic approach to determine the required design and control signals for the robots to generate their desired time-varying shapes.

<p>Soft pneumatic actuators allow compliant force application and movement for a variety of tasks. While most soft actuators have compliance in directions perpendicular to their direction of force application, they are most often analyzed only in their direction of actuation. In this work, we show a characterization of a soft 3D printed bellows actuator that considers shear and axial deformations, modeling both active and passive degrees of freedom. We build a model based on actuator geometry and a parallel linear and torsional spring system which we fit to experimental data in order to obtain the model constants. We demonstrate this model on two complex parallel networks, a delta mechanism and a floating actuator mechanism, and show how this single actuator model can be used to better predict movements in parallel structures of actuators. These results verify that the presented model and modeling approach can be used to speed up the design and simulation of more complex soft robot models by characterizing both active and passive forces of their one degree-of-freedom soft actuators.<br> </p>

Soft robotic systems are becoming increasingly popular as they are generally safer, lighter, and easier to manufacture than their more rigid, traditional counterparts. These advantages allow an increased sense of freedom in both the design and operation of these platforms. In this work, we seek methods of leveraging this freedom to both design and plan motions for two different serial-chain, pneumatically actuated manipulators developed by Pneubotics, a small startup company based in San Francisco. In doing so, we focus primarily on two related endeavors: (1) the optimal kinematic design of these and other similar robots (i.e., choosing link lengths, base positioning, etc.), and (2) the planning of smooth paths in joint space that enable these robots to perform useful tasks. Our method of design optimization employs a genetic algorithm in combination with maximin multi-objective optimization techniques to efficiently generate a diverse set of Pareto optimal designs. This set represents the optimal region of the design space and highlights inherent tradeoffs that designers must make when choosing a particular set of design parameters for manufacture. In our work, we have chosen to optimize inflatable robots to be both dexterous, and to be able to support loads near the ground with limited deflection. We have also applied our framework to optimize a plastic manipulator to perform painting motions. In our approach to motion planning we simultaneously optimize the base position and joint motions of a robot in order to enable its end effector to follow a smooth desired trajectory. While this method of path planning generalizes to any kind of robot, we envision it to be especially applicable to soft robots and other mobile robots that can be quickly and easily repositioned to perform tasks in varying environments. Our method of path planning works by moving a set of virtual robot arms (each representing a single configuration in a sequence) branching from a common base, to a number of assigned target poses associated with a task. Additional goals and hard constraints (including joint limits) are naturally incorporated. The optimization problem at the core of this method is a quadratic program, allowing constrained high-dimensional problems to be solved in very little time. We demonstrate our method by planning and performing painting motion on two different systems. We also demonstrate in simulation how our planner could be used to perform several common tasks including those involving, pick-and-place, wiping and wrapping motions.

This thesis describes the concept of programmable materials with tunable physical properties applicable to soft robots. We present these materials for three major applications in soft robotics: sensing, actuation, and robotic manipulation. The strain sensors recognize the internal stimuli in a soft robot, whereas the conductors collect the sensors’ signals to the control part. In the first part, we want to develop both stretchable strain sensors and conductors from a single material by programming a nanowire network’s electrical property, which we achieve through Electrical Welding (e-welding). We demonstrate the transformation of a Silver Nanowire (AgNW)-polymer sponge from a strain sensor to a stretchable conductor through e-welding. Using this method, we produced a soft hybrid e-skin having both a sensor and conductor from a single material. In the second part, we propose new active actuation solutions by obtaining quick, tunable pressure inside a soft material that we achieve through a liquid-gas phase transition of a stored liquid using an efficient electrode. We discuss the significant design variables to improve the performance and propose a new design for the electrodes, for enhancing actuation speed. We propose using low voltage equipment to trigger the phase transition to produce compact actuation technology for portable applications. Using this method, we produced a portable soft gripper. In the third and last part, we want to develop a simple robotic manipulation technology using a single-chambered soft body instead of a multi-chambered system. We propose using on-demand stiffness change in soft material to control the shape change of a single-chambered soft body. For this, we introduce a new concept of a stiffness tunable hybrid fiber: a fiber with stiff and soft parts connected in a series. We demonstrate a substantial change in membrane stiffness in the fiber through locking/unlocking of the soft part of the fiber. We integrated these fibers into a pneumatically operated single-chambered soft body to control its stiffness for on-demand shape change. If applied together, these three concepts could result in a fully printable, cheap, light, and easily controllable new generation soft robots with augmented functionalities.

<p>While traditional rigid robots are widely used in almost all applications today, their rigidity restricts the use of these robots in environments where interaction with the surroundings or humans is inevitable. This is where soft robots come into play. Due to their compliant and adaptable nature, these robots can safely interact with humans and traverse through unpredictable, cluttered environments. This research focuses on the navigation of a special class of soft growing robots called Vine robots. Vine robots can easily maneuver through tight spaces and rough terrain and have an added advantage of speed over general soft robots. In this work, we develop a model which localizes the Vine robot in an unknown surrounding by giving us the position of the tip of the robot at every instant. The model exploits the passive steering of growing robots using obstacle aided navigation. The robot is sensorized to record the orientation of the its tip and the total length it has grown to. This data along with the force generated on collision with the environment is used to localize the robot in space. The localization model is implemented using the sensor data. The accuracy of this model is then verified by comparing the tip position of the robot we have calculated with its predicted position and the actual position as measured by an overhead camera. It is concluded that the robot can be localized in an environment with a maximum error of 7.65 cm (10\%) when the total length the robot has grown to is 170 cm. </p>

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Soft robots have been used in a wide range of applications from robotic and mechanical engineering to medicine and biomededical field. The growing interest in soft robots comes from their good performance in environments which is not best suited for conventional rigid bodies. Soft robots utilize the compliance, adaptability and flexibility of soft materials and actuation methods to develop highly adaptive structures. Among the soft materials, elastomers are specially popular due to their wide range of elasticity and viscoelasticity. Along with elastomers, textile fabrics are also of high interest for soft robotic applications due to their bendable, flexible, and often stretchable nature. The reinforcement of elastomers with textile fibers results in so-called integrated fiber-elastomer composites (IFEC) which offer a wide variety of properties such as flexibility, strength, fracture toughness and damage resistance. The elastic properties of textile reinforced composites require smart actuators which possess adaptability and deformability. Among existing smart actuators, shape memory alloys (SMA) have been frequently adopted in flexible structures including soft robots. SMAs have sensing and actuation capabilities and are characterized by flexibility and lightness which facilitates their integration into these structures. In this dissertation, the modeling and control of soft prototypes made of IFEC are presented. Shape memory alloys are embedded in the composites for the system actuation. First, the mechanical design and production of three IFEC prototypes are described. For each prototype, a test bench including power and control electronics set-up is designed. Next, mathematical models are developed to analyze the dynamic behavior of the prototypes. The IFEC systems exhibit highly nonlinear behaviour due to SMA hysteresis. For modeling, two different approaches, namely physical modelling and system identification are adopted. In physical modeling, the SMA constitutive and heat transfer equations are incorporated with the composite deflection model. To fully develop the equations, thermal and mechanical parameters of SMA wires are identified experimentally. In the second approach, the mathematical model of the systems is derived from experimental identification and unstructured uncertainty models. Two different control techniques are proposed to compensate the nonlinear behavior of the systems and ensure a robust, fast and precise position tracking. In the first control technique, a proportional integral (PI) controller is designed through robust stability analysis. The second controller is a multivariable PI control which is designed for the prototypes that can move in more than one direction. The performance of the controllers are examined experimentally.

Soft robotic systems have recently been considered as a new approach that is in principle better suited for tasks where safety and adaptability are important. That is because soft materials are inherently compliant and resilient in the event of collisions. They are also lightweight and can be low-cost; in general, soft robots have the potential to achieve many tasks that were not previously possible with traditional robotic systems. In this paper, we propose a new manufacturing process for creating multi-chambered pneumatic actuators and robots. We focus on using fabric as the primary structural material, but plastic films can be used instead of textiles as well. We introduce two different methods to create layered bellows actuators, which can be made with a heat press machine or in an oven. We also describe origami-like actuators with possible corner structures. Moreover, the fabrication process permits the creation of soft and soft/rigid hybrid robotic systems, and enables the easy integration of sensors into these robots. We analyze various textiles that are possibly used with this method, and model bellows actuators including operating force, restoring force, and estimated geometry with multiple bellows. We then demonstrate the process by showing a bellows actuator with an embedded sensor and other fabricated structures and robots. We next present a new design of a multi-DOF soft/rigid hybrid robotic manipulator. It contains a revolute actuator and several roll-pitch actuators which are arranged in series. To control the manipulator, we use a new variant of the piece-wise constant curvature (PCC) model. The robot can be controlled using forward and inverse kinematics with embedded inertial measurement units (IMUs). A bellows actuator, which is a subcomponent of the manipulator, is modeled with a variable-stiffness spring, and we use the model to predict the behavior of the actuator. With the model, the roll-pitch actuator stiffnesses are measured in all directions through applying forces and torques. The stiffness is used to predict the behavior of the end effector. The robotic system introduced achieved errors of less than 5% when compared to the models, and positioning accuracies of better than 1cm. / Doctor of Philosophy / Future robotic systems are expected to deal with many tasks in real-world environments. The natural environment is highly unpredictable and unstructured, making manipulation and locomotion challenging for robots. Robots need to rely on adaptability, reconfigurability, and safety. Soft robotic systems have recently been considered as a new approach that is in principle better suited for tasks where safety and adaptability are important. That is because soft materials are inherently compliant and resilient in the event of collisions. They are also lightweight and can be low-cost; in general, soft robots have the potential to achieve many tasks that were not previously possible with traditional robotic systems. In this paper, we propose a new manufacturing process for creating multi-chambered pneumatic actuators and robots. We focus on using fabric as the primary structural material, but plastic films can be used instead of textiles as well. We introduce two different methods to create layered bellows actuators, which can be made with a heat press machine or household iron, or in an oven. We also describe origami-like actuators with possible corner structures. Moreover, the fabrication process permits the creation of soft and soft/rigid hybrid robotic systems, and enables the easy integration of sensors into these robots. We analyze various textiles that can be used with this method, and make models of bellows actuators including their operating force, restoring force, and estimated geometry with multiple bellows. We then demonstrate the process by showing a bellows actuator with an embedded sensor and other fabricated structures and robots. We next present a new design of a multi-DOF soft/rigid hybrid robotic manipulator. It contains a revolute actuator and several roll-pitch actuators which are arranged in series. To control the manipulator, we use a new variant of the piece-wise constant curvature (PCC) model. The robot can be controlled using forward and inverse kinematics with embedded inertial measurement units (IMUs). A bellows actuator, which is a subcomponent of the manipulator, is modeled with a variable-stiffness spring, and we use the model to predict the behavior of the actuator. With the model, the roll-pitch actuator stiffnesses are measured in all directions through applying forces and torques. The stiffness is used to predict the behavior of the end effector.

Soft lightweight robots provide an inherently safe solution to using robots in unmodeled environments by maintaining safety without increasing cost through expensive sensors. Unfortunately, many practical problems still need to be addressed before soft robots can become useful in real world tasks. Unlike traditional robots, soft robot geometry is not constant but can change with deflation and reinflation. Small errors in a robot's kinematic model can result in large errors in pose estimation of the end effector. This error, coupled with the inherent compliance of soft robots and the difficulty of soft robot joint angle sensing, makes it very challenging to accurately control the end effector of a soft robot in task space. However, this inherent compliance means that soft robots lend themselves nicely to coordinated multi-arm manipulation tasks, as deviations in end effector pose do not result in large force buildup in the arms or in the object being manipulated. Coordinated, multi-arm manipulation with soft robots is the focus of this thesis. We first developed two tools enabling multi-arm manipulation with soft robots: (1) a hybrid servoing control scheme for task space control of soft robot arms, and (2) a general base placement optimization for the robot arms in a multi-arm manipulation task. Using these tools, we then developed and implemented a simple multi-arm control scheme. The hybrid servoing control scheme combines inverse kinematics, joint angle control, and task space servoing in order to reduce end effector pose error. We implemented this control scheme on two soft robots and demonstrated its effectiveness in task space control. Having developed a task space controller for soft robots, we then approached the problem of multi-arm manipulation. The placement of each arm for a multi-arm task is non-trivial. We developed an evolutionary optimization that finds the optimal arm base location for any number of user-defined arms in a user-defined task or workspace. We demonstrated the utility of this optimization in simulation, and then used it to determine the arm base locations for two arms in two real world coordinated multi-arm manipulation tasks. Finally, we developed a simple multi-arm control scheme for soft robots and demonstrated its effectiveness using one soft robot arm, and one rigid robot with low-impedance torque control. We placed each arm base in the pose determined by the base placement optimization, and then used the hybrid servoing controller in our multi-arm control scheme to manipulate an object through two desired trajectories.

<p>Traditional robots and soft robots have often been treated as two distinct options for design, a dichotomy between stiffness and compliance. In reality, they compose two ends of a spectrum, and there has been research to soften traditional robots and stiffen soft robots. The latter option has seen a large variety of techniques to actively and selectively create stiffness in an otherwise soft robot. The common disadvantage concerning all of them is the need for constant energy input. In this work, a first-of-its-kind method for a permanent stiffness of a growing robot is explored and tested.</p> <p>First, I show the qualitative and quantitative testing of the stiffening method, expanding insulation foam, both by itself and when applied to a vine robot. With this knowledge, I investigate a design to apply the foam to a growing robot as it moves, taking advantage of the properties of the foam to coat a vine robot as needed. This selective foam placement unlocks various unique capabilities like adhering to its environment, imparting & resisting large forces, and isolating sections of its body. Finally, these traits are highlighted in three demonstrations, proving the efficacy of this unique method as well as affirming the utility of permanently stiffening a soft robot. In the future, the work in this thesis can help open the way for permanent deployable robotic structures and soft robots in roles more traditionally used for rigid robots.</p>