Browsing by Author "Zhao, Jianguo, advisor"
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Item Open Access Biologically inspired perching for aerial robots(Colorado State University. Libraries, 2021) Zhang, Haijie, author; Zhao, Jianguo, advisor; Bradley, Thomas H., committee member; Pasricha, Sudeep, committee member; Guzik, Stephen, committee memberMicro Aerial Vehicles (MAVs) are widely used for various civilian and military applications (e.g., surveillance, search, and monitoring, etc.); however, one critical problem they are facing is the limited airborne time (less than one hour) due to the low aerodynamic efficiency, low energy storage capability, and high energy consumption. To address this problem, mimicking biological flyers to perch onto objects (e.g., walls, power lines, or ceilings) will significantly extend MAVs' functioning time for surveillance or monitoring related tasks. Successful perching for aerial robots, however, is quite challenging as it requires a synergistic integration of mechanical and computational intelligence. Mechanical intelligence means mechanical mechanisms to passively damp out the impact between the robot and the perching object and robustly engage the robot to the perching objects. Computational intelligence means computation algorithms to estimate, plan, and control the robot's motion so that the robot can progressively reduce its speed and adjust its orientation to perch on the objects with a desired velocity and orientation. In this research, a framework for biologically inspired perching is investigated, focusing on both computational and mechanical intelligence. Computational intelligence includes vision-based state estimation and trajectory planning. Unlike traditional flight states such as position and velocity, we leverage a biologically inspired state called time-to-contact (TTC) that represents the remaining time to the perching object at the current flight velocity. A faster and more accurate estimation method based on consecutive images is proposed to estimate TTC. Then a trajectory is planned in TTC space to realize the faster perching while satisfying multiple flight and perching constraints, e.g., maximum velocity, maximum acceleration, and desired contact velocity. For mechanical intelligence, we design, develop, and analyze a novel compliant bistable gripper with two stable states. When the gripper is open, it can close passively by the contact force between the robot and the perching object, eliminating additional actuators or sensors. We also analyze the bistability of the gripper to guide and optimize the design of the gripper. At the end, a customized MAV platform of size 250 mm is designed to combine computational and mechanical intelligence. A Raspberry Pi is used as the onboard computer to do vision-based state estimation and control. Besides, a larger gripper is designed to make the MAV perch on a horizontal rod. Perching experiments using the designed trajectories perform well at activating the bistable gripper to perch while avoiding large impact force which may damage the gripper and the MAV. The research will enable robust perching of MAVs so that they can maintain a desired observation or resting position for long-duration inspection, surveillance, search, and rescue.Item Open Access Design, modeling, and optimization of 3D printed compliant mechanisms with applications to miniature walking robots(Colorado State University. Libraries, 2018) DeMario, Anthony R., author; Zhao, Jianguo, advisor; Stansloski, Mitchell, committee member; Maciejewski, Anthony, committee memberMiniature robots have many applications ranging from military surveillance to search and rescue assistance in disaster areas. Traditionally, fabrication of these robots has been labor intensive, time-consuming, and expensive. This thesis proposes to leverage recent advances in 3D printing technology to fabricate centimeter-scale walking robots utilizing compliant elements printed directly into the walking mechanisms in replacement of traditional revolute joints or rigid links. The ability to design around the capabilities of 3D printers and novel material choices gives miniature robots the ability to have multiple functions in the same mechanism, reduces the overall number of parts that must be assembled to make a functional robot, and decrease the time and cost of prototyping. This thesis details three areas of study for compliant mechanisms with applications to walking robots. First, we utilize multi-material 3D printing to fabricate a miniature walking robot (49 x 38 x 25mm) that directly replaces the traditional revolute joints in the designed walking mechanism with a custom, soft joint. Some links are also printed with soft materials to enhance the robustness and durability of the robot. Along with design and testing of the robot, we develop two numerical models to simulate the effects of the soft elements on the mechanism trajectory. Second, we leverage the numerical models to optimize the design of the walking mechanism to produce a trajectory similar to that of the same mechanism using all revolute joints. Third, we redesign the original robot to utilize a conductive polylactic acid (PLA) material to 3D print linkages that allow for changing joints locations by softening the desired part through applied electricity. This variable joint mechanism can create multiple trajectories without changing the mechanical structure, therefore creating a multi-functional compliant mechianism. Such capabilities are demonstrated throughwalking on the ground and grasping objects using the same leg mechanism.Item Open Access Modeling of twisted and coiled artificial muscle for actuation and self-sensing(Colorado State University. Libraries, 2018) Abbas, Ali, author; Zhao, Jianguo, advisor; Bradley, Thomas, committee member; Maciejewski, Anthony, committee memberSoft robots are a new type of robots with deformable bodies and muscle-like actuations, which are fundamentally different from traditional robots with rigid links and motor-based actuators. Owing to their elasticity, soft robots outperform rigid ones in safety, maneuverability, and adaptability. With their advantages, many soft robots have been developed for manipulation and locomotion in recent years. Nevertheless, two issues prevent the wide applications of developed soft robots: cumbersome actuation methods (e.g., pneumatics) and limited sensing capability to feedback the robot's shape. To address these two issues, this thesis leverages a recently discovered twisted and coiled artificial muscle for soft robots. This artificial muscle can generate large force and displacement; moreover, we recently found that it has self-sensing capability, i.e., its electrical resistance will increase if the muscle is elongated by an external force. With the dual actuation and self-sensing capability, we expect to accomplish closed-loop control of soft robots for precise motion without external sensors, potentially solving the two issues for existing soft robots. This thesis will focus on three aspects for the twisted and coiled artificial muscle. First, we model the actuation from a physics perspective. Such a model utilizes parameters related to the working principle and material properties of the actuator, eliminating the requirements for tedious system identifications. Experiments are conducted to verify the proposed model, and the results demonstrate that the proposed model can predict the static performance and dynamic response for the muscle. Second, we test and model the sensing capability of the artificial muscle. Specifically, we establish a physics-based model to predict the external force and the displacement if the resistance is given and experimentally validate its correctness. Third, we apply the actuation and sensing of the artificial muscle to soft robots. To demonstrate we can leverage the muscle to actuate soft robots, we fabricate a soft manipulator with multiple muscles as well as a robotic fish tail. To demonstrate the sensing capability, we embed the muscle into soft materials and successfully measure two curvatures of a two-segment soft robot. Based on the work presented in this thesis, our future work will integrate the actuation and sensing capability of the twisted and coiled artificial muscle to enable closed-loop shape control of soft robots.Item Open Access Modeling, simulation, and control of soft robots(Colorado State University. Libraries, 2019) Pawlowski, Ben, author; Zhao, Jianguo, advisor; Puttlitz, Christian, committee member; Anderson, Charles, committee memberSoft robots are a new type of robot with deformable bodies and muscle-like actuations, which are fundamentally different from traditional robots with rigid links and motor-based actuators. Owing to their elasticity, soft robots outperform rigid ones in safety, maneuverability, and adaptability. With their advantages, many soft robots have been developed for manipulation and locomotion in recent years. However, the current state of soft robotics has significant design and development work, but lags behind in modeling and control due to the complex dynamic behavior of the soft bodies. This complexity prevents a unified dynamics model that captures the dynamic behavior, computationally-efficient algorithms to simulate the dynamics in real-time, and closed-loop control algorithms to accomplish desired dynamic responses. In this thesis, we address the three problems of modeling, simulation, and control of soft robots. For the modeling, we establish a general modeling framework for the dynamics by integrating Cosserat theory with Hamilton's principle. Such a framework can accommodate different actuation methods (e.g., pneumatic, cable-driven, artificial muscles, etc.). To simulate the proposed models, we develop efficient numerical algorithms and implement them in C++ to simulate the dynamics of soft robots in real-time. These algorithms consider qualities of the dynamics that are typically neglected (e.g., numerical damping, group structure). Using the developed numerical algorithms, we investigate the control of soft robots with the goal of achieving real-time and closed-loop control policies. Several control approaches are tested (e.g., model predictive control, reinforcement learning) for a few key tasks: reaching various points in a soft manipulator's workspace and tracking a given trajectory. The results show that model predictive control is possible but is computationally demanding, while reinforcement learning techniques are more computationally effective but require a substantial number of training samples. The modeling, simulation, and control framework developed in this thesis will lay a solid foundation to unleash the potential of soft robots for various applications, such as manipulation and locomotion.Item Open Access Soft and shape morphing robots driven by twisted-and-coiled actuators(Colorado State University. Libraries, 2022) Sun, Jiefeng, author; Zhao, Jianguo, advisor; Maciejewski, Anthony, committee member; Gao, Xinfeng, committee member; Yourdkhani, Mostafa, committee memberSoft robots are a new type of robot with deformable bodies and muscle-like actuation, which are fundamentally different from traditional robots with rigid links and motor-based actuators. Owing to their elasticity, soft robots outperform rigid ones in safety, maneuverability, and adaptability. With their advantages, many soft robots have been developed for manipulation and locomotion in recent years. To enable their unique capabilities, soft robots require a key component—the actuator. Many different actuators have been used, including the conventional pneumatic-driven and cable-driven methods, as well as several novel approaches proposed recently such as combustion, dielectric elastomers, chemical reactions, liquid–vapor transition, liquid crystal elastomer, and shape memory alloy. Besides existing actuation approaches, another promising actuator for soft robots is the twisted-and-coiled actuator (TCA). Compared with existing actuation methods, TCAs exhibit several unique characteristics: like large energy density and being directly actuated by electricity with a small voltage. All of these characteristics will potentially enable small-scale and untethered soft robots that in general are difficult to be accomplished by pneumatic and tendon-driven methods. Further, unlike shape memory alloys, TCAs are intrinsically soft, making it possible to embed them in any shape inside a soft body to generate versatile motion. To better actuate soft robots with TCAs, we introduce a novel fabrication technique of contraction TCAs that will have uniform initial gaps between neighboring coils. In this case, they can contract larger than 48% without a preload, termed free stroke. We also characterize such a TCA and compare it with self-coiled TCAs. Besides the free stroke property, the TCA can also be directly used as a sensor that provides its displacement information. To better design, optimize, and control TCAs for various applications, we developed a physics-based model based on TCAs' physical parameters as opposed to system identification methods, since such physics-based models are expected to be a general model for different types of TCAs (self-coiled, free-stroke, conical) We demonstrate soft robots with programmable motions by placing TCAs in different shapes inside a soft body. Specifically, we embed TCAs in a curved U shape, a helical shape, and straight shapes in parallel to enable three different motions: two-dimensional bending, twisting, and three-dimensional bending. We also combine the three motions to demonstrate a completely soft robotic arm that mimics a human forearm. A model is also developed to simulate the TCA-driven soft robots. The framework can model 1) the complicated routes of multiple TCAs in a soft body and 2) the coupling effect between the soft body and the TCAs during their actuation process. When not actuated, a TCA in the soft body is an antagonistic elastic element that restrains the magnitude of the motion and increases the stiffness of the robot. By stacking several modules together, we simulate the sequential motion of a soft robotics arm with three-dimensional bending, twisting, and grasping motion. The presented modeling and simulation approach will facilitate the design, optimization, and control of soft robots driven by TCAs or other types of artificial muscles. Finally, we design shape morphing robots that can morph the shape of their bodies to adapt to a different environment. These robots can be built with shape-morphing modules. A shape-morphing module has a variable stiffness element that allows it to switch between soft and rigid states. While it is in a soft state, it can morph to different configurations driven by TCAs. We demonstrate robots built with these modules can morph to different shapes that facilitate grasping and locomotion.Item Open Access The manufacturing and soft robotic applications of free stroke twisted and coiled actuators(Colorado State University. Libraries, 2022) Tighe, Brandon Z., author; Zhao, Jianguo, advisor; Endeshaw, Haile, committee member; Simske, Steve, committee memberInspired by biological systems (e.g., octopus), soft robots made from soft materials outperform traditional rigid robots in terms of safety and adaptivity because of their compliant and deformable bodies. To enable a soft robot's unique capabilities, they require a key component—the actuator. Many different actuators have been used, including the conventional pneumatic-driven and cable driven methods, and also several emerging approaches, like dielectric elastomers, liquid crystal elastomers, and shape memory alloys. Besides existing actuation approaches, another promising actuator for soft robots is the twisted-and-coiled actuator (TCA), which can be conveniently fabricated by continuously twisting polymer fibers into a coiled spring-like shape. In this thesis, we investigate free stroke TCAs (i.e., TCAs that can produce significant displacements without preloading). We first describe a customized machine that can automatically fabricate TCAs with free strokes by twisting a polymer fiber and then coiling the twisted fiber along a mandrel with a guide channel, which is made by wrapping a small copper wire helically about a larger one. After that, we discuss the characterization and evaluation of the fabricated TCAs. We also apply free stroke TCAs to two different soft robotic systems. The first one is a spherical tensegrity robot which resembles a tensegrity structure, a compliant yet stable structure made of rigid rods and elastic cables. By replacing the elastic cables with TCAs, we can actuate TCAs to shift the robot's center of gravity to generate rolling locomotion. The second application is a shape morphing quadrupedal robot with multiple modes of locomotion. By actively morphing the robot's body shape, we demonstrate different locomotion modes for the same robot, including walking on flat ground, crawling below a gap, and climbing across a bridge. Demonstrations for the tensegrity robot and shape morphing robot will facilitate future biologically inspired adaptive robotic systems to actively adapt their morphologies and behaviors to different environments.