Soft robotic platforms are becoming increasingly popular as they are generally safer, lighter, and easier to manufacture than their more rigid, heavy, traditional counterparts. These soft platforms, while inherently safer, come with significant drawbacks. Their compliant components are more difficult to model, and their underdamped nature makes them difficult to control. Additionally, they are so lightweight that a payload of just a few pounds has a significant impact on the manipulator dynamics. This thesis presents novel methods for addressing these issues. In previous research, Model Predictive Control has been demonstrably useful for joint angle control for these soft robots, using a rigid inverted pendulum model for each link. A model describing the dynamics of the entire arm would be more desirable, but with high Degrees of Freedom it is computationally expensive to optimize over such a complex model. This thesis presents a method for simplifying and linearizing the full-arm model (the Coupling-Torque method), and compares control performance when using this method of linearization against control performance for other linearization methods. The comparison shows the Coupling-Torque method yields good control performance for manipulators with seven or more Degrees of Freedom. The decoupled nature of the Coupling-Torque method also makes adaptive control, of the form described in this thesis, easier to implement. The Coupling-Torque method improves performance when the dynamics are known, but when a payload of unknown mass is attached to the end effector it has a significant impact on the dynamics. Adaptive Control is needed at this point to compensate for the model's poor approximation of the system. This thesis presents a method of layering Model Reference Adaptive Control in concert with Model Predictive Control that improves control performance in this scenario. The adaptive controller modifies dynamic parameters, which are then delivered to the optimizer, which then returns inputs for the system that take all of this information into account. This method has been shown to reduce step input tracking error by 50% when implemented on the soft robot.

Inflatable robots with pneumatic actuation are naturally lightweight and compliant. Both of these characteristics make a robot of this type better suited for human environments where unintentional impacts will occur. The dynamics of an inflatable robot are complex and dynamic models that explicitly allow variable stiffness control have not been well developed. In this thesis, a dynamic model was developed for an antagonistic, pneumatically actuated joint with inflatable links.The antagonistic nature of the joint allows for the control of two states, primarily joint position and stiffness. First a model was developed to describe the position states. The model was used with model predictive control (MPC) and linear quadratic control (LQR) to control a single degree of freedom platform to within 3° of a desired angle. Control was extended to multiple degrees of freedom for a pick and place task where the pick was successful ten out of ten times and the place was successful eight out of ten times.Based on a torque model for the joint which accounts for pressure states that was developed in collaboration with other members of the Robotics and Dynamics Lab at Brigham Young University, the model was extended to account for the joint stiffness. The model accounting for position, stiffness, and pressure states was fit to data collected from the actual joint and stiffness estimation was validated by stiffness measurements.Using the stiffness model, sliding mode control (SMC) and MPC methods were used to control both stiffness and position simultaneously. Using SMC, the joint stiffness was controlled to within 3 Nm/rad of a desired trajectory at steady state and the position was controlled to within 2° of a desired position trajectory at steady state. Using MPC,the joint stiffness was controlled to within 1 Nm/rad of a desired trajectory at steady state and the position was controlled to within 2° of a desired position trajectory at steady state. Stiffness control was extended to multiple degrees of freedom using MPC where each joint was treated as independent and uncoupled. Controlling stiffness reduced the end effecter deflection by 50% from an applied load when high stiffness (50 Nm/rad) was used rather than low stiffness (35 Nm/rad).This thesis gives a state space dynamic model for an inflatable, pneumatically actuated joint and shows that the model can be used for accurate and repeatable position and stiffness control with stiffness having a significant effect.

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.

Legged robots have the potential to cover terrain not accessible to wheel-based robots and vehicles. This makes them better suited to perform tasks, such as search and rescue, in real-world unstructured environments. Pneumatically-actuated, compliant robots are also more suited than their rigid counterparts to work in real-world unstructured environments with humans where unintentional contact may occur. This thesis seeks to combine the benefits of these two type of robots by implementing design methods to aid in the design choice of a 16 degree of freedom (DoF) compliant, continuum-joint quadruped. This work focuses on the design optimization, especially the definition of design metrics, for this type of robot. The work also includes the construction and closed-loop control of a four-DoF continuum-joint leg used to validate design methods.We define design metrics for legged robot metrics that evaluate their ability to traverse unstructured terrain, carry payloads, find stable footholds, and move in desired directions. These design metrics require a sampling of a legged-robot's complete configuration space. For high-DoF robots, such as the 16-DoF in evaluated in this work, the evaluation of these metrics become intractable with contemporary computing power. Therefore, we present methods that can be used to simplify and approximate these metrics. These approximations have been validated on a simulated four-DoF legged robot where they can tractably be compared against their full counterparts.Using the approximations of the defined metrics, we have performed a multi-objective design optimization to investigate the ten-dimensional design space of a 16-DoF compliant, continuum-joint quadruped. The design variables used include leg link geometry, robot base dimensions, and the leg mount angles. We have used an evolutionary algorithm as our optimization method which converged on a Pareto front of optimal designs. From these set of designs, we are able to identify the trade-offs and design differences between robots that perform well in each of the different design metrics. Because of our approximation of the metrics, we were able to perform this optimization on a supercomputer with 28 cores in less than 40 hours.We have constructed a 1.3 m long continuum-joint leg from one of the resulting quadruped designs of the optimization. We have implemented configuration estimation and control and force control on this leg to evaluate the leg payload capability. Using these controllers, we have conducted an experiment to compare the leg's ability to provide downward force in comparison with its theoretical payload capabilities. We then demonstrated how the torque model used in the calculation of payload capabilities can accurately calculate trends in force output from the leg.

[pt] Sistemas pneumáticos são equipamentos leves, baratos, limpos e de baixo risco, sendo apropriados para aplicações que necessitem de força e rapidez de resposta. Por outro lado, esse tipo de sistema apresenta restrições devido à principal característica do ar: sua compressibilidade confere efeitos não lineares ao sistema, desde um escoamento turbulento pelas válvulas de controle até sua atuação dentro do cilindro – a qual inclui alta sensibilidade ao atrito e volumes inativos durante o curso do pistão. Essas características particulares dificultam seu controle e posicionamento preciso e limitam sua aplicação, principalmente considerando seu emprego em um mecanismo tipo Plataforma de Stewart em escala reduzida. No presente trabalho apresenta-se a modelagem, simulação computacional e análise experimental do comportamento dinâmico de um sistema de atuação pneumático que inclui uma válvula de controle de vazão não convencional, composta de quatro válvulas proporcionais, e um atuador com haste simples de dupla ação. O objetivo deste trabalho é, baseado nos resultados experimentais, determinar as características desses componentes para desenvolver estratégias de controle em tempo real capazes de minimizar os efeitos das não linearidades típicas, visando sua utilização no mecanismo anteriormente mencionado. / [en] Pneumatic equipment is lightweight, cheap, clean and low-risk, being suitable for applications that require strength and high responsiveness. Nevertheless, this type of system has some limitations due to the air main feature: its compressibility results in nonlinear effects in the system, from the turbulent flow control valves to its performance inside the cylinder - which includes high sensitivity to friction and dead volumes during the stroke piston. These particular characteristics make its control and precise positioning difficult, limiting its application, especially when considered its use in a mechanism such as a Stewart Platform in a reduced scale. The present paper presents the modeling, computational simulation and experimental analysis of the dynamic behavior of a pneumatic actuation system that includes an unconventional flow control valve, consisting of four proportional valves, and a double acting single rod actuator. The final goal of this work is to, based on experimental results, determine the characteristics of these components in order to develop real-time control strategies which can minimize the effects of those typical nonlinearities for their use in the mechanism mentioned above.