This dissertation studies the methods to enhance the performance of foldable robots manufactured by laminated techniques. This class of robots are unique in their manufacturing process, which involves cutting and staking up thin layers of different materials with various stiffness. While inheriting the advantages of soft robots -- low weight, affordable manufacturing cost and a fast prototyping process -- a wider range of actuators is available to these mechanisms, while modeling their behavior requires less computational cost.The fundamental question this dissertation strives to answer is how to decode and leverage the effect of material stiffness in these robots. These robots' stiffness is relatively limited due to their slender design, specifically at larger scales. While compliant robots may have inherent advantages such as being safer to work around, this low rigidity makes modeling more complex. This complexity is mostly contained in material deformation since the conventional actuators such as servo motors can be easily leveraged in these robots. As a result, when introduced to real-world environments, efficient modeling and control of these robots are more achievable than conventional soft robots. Various approaches have been taken to design, model, and control a variety of laminate robot platforms by investigating the effect of material deformation in prototypes while they interact with their working environments. The results obtained show that data-driven approaches such as experimental identification and machine learning techniques are more reliable in modeling and control of these mechanisms. Also, machine learning techniques for training robots in non-ideal experimental setups that encounter the uncertainties of real-world environments can be leveraged to find effective gaits with high performance. Our studies on the effect of stiffness of thin, curved sheets of materials has evolved into introducing a new class of soft elements which we call Soft, Curved, Reconfigurable, Anisotropic Mechanisms (SCRAMs). Like bio-mechanical systems, SCRAMs are capable of re-configuring the stiffness of curved surfaces to enhance their performance and adaptability. Finally, the findings of this thesis show promising opportunities for foldable robots to become an alternative for conventional soft robots since they still offer similar advantages in a fraction of computational expense.

The majority of drones are extremely simple, their functions include flight and sometimes recording video and audio. While drone technology has continued to improve these functions, particularly flight, additional functions have not been added to mainstream drones. Although these basic functions serve as a good framework for drone designs, it is now time to extend off from this framework. With this Honors Thesis project, we introduce a new function intended to eventually become common to drones. This feature is a grasping mechanism that is capable of perching on branches and carrying loads within the weight limit. This concept stems from the natural behavior of many kinds of insects. It paves the way for drones to further imitate the natural design of flying creatures. Additionally, it serves to advocate for dynamic drone frames, or morphing drone frames, to become more common practice in drone designs.

While many 3D printed structures are rigid and stationary, the potential for complex geometries offers a chance for creative and useful motion. Printing structures larger than the print bed, reducing the need for support materials, maintaining multiple states without actuation, and mimicking origami folding are some of the opportunities offered by 3D printed hinges. Current efforts frequently employ advanced materials and equipment that are not available to all users. The purpose of this project was to develop a parametric, print-in-place, self-locking hinge that could be printed using very basic materials and equipment. Six main designs were developed, printed, and tested for their strength in maintaining a locked position. Two general design types were used: 1) sliding hinges and 2) removable pin hinges. The test results were analyzed to identify and explain the causes of observed trends. The amount of interference between the pin vertex and knuckle hole edge was identified as the main factor in hinge strength. After initial testing, the designs were modified and applied to several structures, with successful results for a collapsible hexagon and a folding table. While the initial goal was to have one CAD model as a final product, the need to evaluate tradeoffs depending on the exact application made this impossible. Instead, a set of design guidelines was created to help users make strategic decisions and create their own design. Future work could explore additional scaling effects, printing factors, or other design types.

This thesis aims to design of wings for a laminate biped robot for providing locomotion stabilization during jump gliding. The wings are designed to collapse down during the jumping phase to maximize jump height and deployed back for gliding phase using anisotropic buckling in tape spring hinges. The project aims to develop a reliable dynamics model which can be utilized for design and evaluation of optimized systems for jump-gliding. The aerodynamic simulations are run on a vortex-lattice code which provides numeric simulations of the defined geometric bodies. The aerodynamic simulations assist in improving the design parameters such as planform, camber and twist to achieve the best possible Coefficient of Lift for maximizing glide distance. The aerodynamic simulation output is then plugged into a dynamics model built in Python, which is validated and correlated with experimental testing of a key wing designs. The experimental results are then utilized to improve the dynamics model and obtain better designs for improved performance. The simulation model informs the aerodynamic design of wings for sustaining glide for the biped platform and maximizing glide length to increase range.

Multi-material fabrication allows for the creation of individual parts composed of several materials with distinct properties, providing opportunities for integrating mechanisms into monolithic components. Components produced in this manner will have material boundaries which may be points of failure. However, the unique capabilities of multi-material fabrication allow for the use of graded material transitions at these boundaries to mitigate the impact of abrupt material property changes.

The goal of this work is to identify methods of creating graded material transitions that can improve the ultimate tensile strength of a multi-material component while maintaining other model properties. Particular focus is given towards transitions that can be produced using low cost manufacturing equipment. This work presents a series of methods for creating graded material transitions which include previously established transition types as well as several novel techniques. Test samples of each transition type were produced using additive manufacturing and their performance was measured. It is shown that some types of transitions can increase the ultimate strength of a part, while others may introduce new stress concentrations that reduce performance. This work then presents a method for adjusting the elastic modulus of a component to which graded material transitions have been added to allow the original design properties to be met.

This paper describes the attempt of designing and building a two wheeled platform that is inherently unstable and discovering what tail design is suitable for stabilizing the platform. The platform is a 3D printed box that carries an Arduino, breadboard, MPU6050, a battery and a servo. This box is connected to two continuous servo motors (one on each side) that are attached to wheels, the breadboard and Arduino are mounted on the inside and the MPU6050 is mounted on the back of the base. The MPU6050 collects the data. In the program, that data will be the position of the accelerometer’s x-axis and that data will be sent to the servo motor with the tail for the controls aspect.

This thesis presents a kit of materials intended to present students with a glimpse of what engineering entails by guiding them through building engineering projects similar to what is in the real world. The objective of this project is to pique the interest of children by introducing them to lesser known engineering related topics, and increasing their literacy of terms and methods engineers use to solve problems. The effectiveness of the kit’s content and teaching methods was tested in a classroom of 6th graders and was measured using the responses from surveys handed out. I found that kit did in fact positively lead to a change in the way the students perceived engineering, and it taught students about new engineering related topics. Students were capable of completing difficult tasks of wiring and coding successfully through the use of detailed instruction. However, the instructions were seen in two opposing views of either being too overwhelming or more guidance was necessary.

The goal of reinforcement learning is to enable systems to autonomously solve tasks in the real world, even in the absence of prior data. To succeed in such situations, reinforcement learning algorithms collect new experience through interactions with the environment to further the learning process. The behaviour is optimized by maximizing a reward function, which assigns high numerical values to desired behaviours. Especially in robotics, such interactions with the environment are expensive in terms of the required execution time, human involvement, and mechanical degradation of the system itself. Therefore, this thesis aims to introduce sample-efficient reinforcement learning methods which are applicable to real-world settings and control tasks such as bimanual manipulation and locomotion. Sample efficiency is achieved through directed exploration, either by using dimensionality reduction or trajectory optimization methods. Finally, it is demonstrated how data-efficient reinforcement learning methods can be used to optimize the behaviour and morphology of robots at the same time.

What if there is a way to integrate prosthetics seamlessly with the human body and robots could help improve the lives of children with disabilities? With physical human-robot interaction being seen in multiple aspects of life, including industry, medical, and social, how these robots are interacting with human becomes even more important. Therefore, how smoothly the robot can interact with a person will determine how safe and efficient this relationship will be. This thesis investigates adaptive control method that allows a robot to adapt to the human's actions based on the interaction force. Allowing the relationship to become more effortless and less strained when the robot has a different goal than the human, as seen in Game Theory, using multiple techniques that adapts the system. Few applications this could be used for include robots in physical therapy, manufacturing robots that can adapt to a changing environment, and robots teaching people something new like dancing or learning how to walk after surgery.

The experience gained is the understanding of how a cost function of a system works, including the tracking error, speed of the system, the robot’s effort, and the human’s effort. Also, this two-agent system, results into a two-agent adaptive impedance model with an input for each agent of the system. This leads to a nontraditional linear quadratic regulator (LQR), that must be separated and then added together. Thus, creating a traditional LQR. This new experience can be used in the future to help build better safety protocols on manufacturing robots. In the future the knowledge learned from this research could be used to develop technologies for a robot to allow to adapt to help counteract human error.