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Comparison of Evolutionary Strategies and Reinforcement Learning Algorithms on Custom and Non-Conventional Environment

Description

Reinforcement Learning(RL) algorithms have made a remarkable contribution in the eld of robotics and training human-like agents. On the other hand, Evolutionary Algorithms(EA) are not well explored and promoted to use in the robotics field. However, they have an excellent potential to perform well. In thesis work, various RL learning…

Reinforcement Learning(RL) algorithms have made a remarkable contribution in the eld of robotics and training human-like agents. On the other hand, Evolutionary Algorithms(EA) are not well explored and promoted to use in the robotics field. However, they have an excellent potential to perform well. In thesis work, various RL learning algorithms like Q-learning, Deep Deterministic Policy Gradient(DDPG), and Evolutionary Algorithms(EA) like Harmony Search Algorithm(HSA) are tested for a customized Penalty Kick Robot environment. The experiments are done with both discrete and continuous action space for a penalty kick agent. The main goal is to identify which algorithm suites best in which scenario. Furthermore, a goalkeeper agent is also introduced to block the ball from reaching the goal post using the multiagent learning algorithm.

ContributorsTrivedi, Maitry Ronakbhai (Author) / Amor, Heni Ben (Thesis advisor) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)

Created2021

Data-driven Control of Nonlinear Dynamics Systems

Description

This research proposes some new data-driven control methods to control a nonlinear dynamic model. The nonlinear dynamic model linearizes by using the Koopman theory. The Koopman operator is the most important part of designing the Koopman theory. The data mode decomposition (DMD) is used to obtain the Koopman operator. The…

This research proposes some new data-driven control methods to control a nonlinear dynamic model. The nonlinear dynamic model linearizes by using the Koopman theory. The Koopman operator is the most important part of designing the Koopman theory. The data mode decomposition (DMD) is used to obtain the Koopman operator. The proposed data-driven control method applies to different nonlinear systems such as microelectromechanical systems (MEMS), Worm robots, and 2 degrees of freedom (2 DoF) robot manipulators to verify the performance of the proposed method. For the MEMS gyroscope, three control methods are applied to the linearized dynamic model by the Koopman theory: linear quadratic regulator (LQR), compound fractional PID sliding mode control, and fractional order PID controller tuned with bat algorithm. For the Worm robot, an LQR controller is proposed to control the linearized dynamic model by the Koopman theory. A new fractional sliding mode control is proposed to control the 2 DoF arm robot. All the proposed controllers applied to the linearized dynamic model by the Kooman theory are compared with some conventional proposed controllers such as PID, sliding mode control, and conventional fractional sliding mode control to verify the performance of the proposed controllers. Simulation results validate their performance in high tracking performance, low tracking error, low frequency, and low maximum overshoot.

ContributorsRahmani, Mehran (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / C. Subramanian, Susheelkumar (Committee member) / Arizona State University (Publisher)

Created2023

Autonomous System Control of Multiple Robotic Arms Collaboration via Machine Learning

Description

Multiple robotic arms collaboration is to control multiple robotic arms to collaborate with each other to work on the same task. During the collaboration, theagent is required to avoid all possible collisions between each part of the robotic arms. Thus, incentivizing collaboration and preventing collisions are the two principles which are followed…

Multiple robotic arms collaboration is to control multiple robotic arms to collaborate with each other to work on the same task. During the collaboration, theagent is required to avoid all possible collisions between each part of the robotic arms. Thus, incentivizing collaboration and preventing collisions are the two principles which are followed by the agent during the training process. Nowadays, more and more applications, both in industry and daily lives, require at least two arms, instead of requiring only a single arm. A dual-arm robot satisfies much more needs of different types of tasks, such as folding clothes at home, making a hamburger in a grill or picking and placing a product in a warehouse. The applications done in this paper are all about object pushing. This thesis focuses on how to train the agent to learn pushing an object away as far as possible. Reinforcement Learning (RL), which is a type of Machine Learning (ML), is then utilized in this paper to train the agent to generate optimal actions. Deep Deterministic Policy Gradient (DDPG) and Hindsight Experience Replay (HER) are the two RL methods used in this thesis.

ContributorsLin, Steve (Author) / Ben Amor, Hani (Thesis advisor) / Redkar, Sangram (Committee member) / Zhang, Yu (Committee member) / Arizona State University (Publisher)

Created2023

Embodied Wearables: The Role of Proprioception in Exoskeleton Design.

Description

This work endeavors to lay a solid foundation for the exploration and the considerations of exoskeletons, exosuits, and medical devices concerning proprioceptive feedback. This investigation is situated at the nexus of engineering, neuroscience, and rehabilitation medicine, striving to cultivate a holistic understanding of how mechanical augmentation, interfaced synergistically with human…

This work endeavors to lay a solid foundation for the exploration and the considerations of exoskeletons, exosuits, and medical devices concerning proprioceptive feedback. This investigation is situated at the nexus of engineering, neuroscience, and rehabilitation medicine, striving to cultivate a holistic understanding of how mechanical augmentation, interfaced synergistically with human proprioception, can foster enhanced mobility and safety. This is especially pertinent for individuals with compromised motor functions.British Neurologist Oliver Wolf Sacks in 1985 published “The Man who Mistook His Wife for a Hat” a series of his most memorable neurological case describing the brain's strangest pathways. One of these cases is “The Disembodied Lady”, Christina a 27-year-old woman that lost entirely the sense of proprioception due to polyneuropathy. This caused her to not be able to control her body, and she declares that “I feel the wind on my arms and face, and then I know, faintly, I have arms and a face. It’s not the real thing, but it’s something—it lifts this horrible, dead veil for a while. ” Finally, she was able to control her body using vision alone. Dr. Sacks introduced, for the first time, the importance of proprioception, as the sense of position of body parts relative to other parts of the body, to western culture. This document’s mission is to identify unexplored concepts in the literature regarding exoskeletons, wearables and assistive technology and a user’s proprioception, embodiment and utilization when wearing devices. Dr. Philipp Beckerle suggests the need to research the connections between wearable hardware and human sense of proprioception. He also emphasizes the need for functional assessment protocols for wearables devices and the role of embodiment. He criticizes the current commercially available upper-limb prostheses since they only restore limited functions and therefore impede embodiment. This document’s goal is to identify operative solutions through the adaptation of existing technologies and to use effective solutions to improve the quality of life of people suffering from pathologies or traumatic injuries.

ContributorsVignola, Claudio (Author) / Sugar, Thomas (Thesis advisor) / Redkar, Sangram (Committee member) / McDaniels, Troy (Committee member) / Arizona State University (Publisher)

Created2023

Multi Robot Coordination In Unstructured Environment

Description

In today’s modern world, industrial robots are utilized in hazardous working condi-tions across all industries, including the renewable energy industry. Robot control systems and sensors receive and transmit information and data obtained from the users. Over the last ten years, unmanned vehicles have developed into a subject of interest for a variety of…

In today’s modern world, industrial robots are utilized in hazardous working condi-tions across all industries, including the renewable energy industry. Robot control systems and sensors receive and transmit information and data obtained from the users. Over the last ten years, unmanned vehicles have developed into a subject of interest for a variety of research institutions. Technology breakthroughs are redefin- ing disaster relief, search-and-rescue(SAR) and salvage operations’ for aerial robotic systems as well as terrestrial and marine ones. A team of collaborative robots is required for the challenging environments, such as space construction, and disaster relief. These robots will have to make trade-offs between mobility and capabilities owing to cost, power, and size constraints. Task execution in numerous areas may de- mand for robot collaboration in order to optimize team performance. An analysis of collaborative Unmanned Aerial Vehicle(UAV) and Unmanned Ground Vehicle(UGV) systems is one of the main components of this thesis. UAV/UGV collaborative frame- works and methods have been presented for reaching or monitoring moving human targets, a stated set-point for a mobile UGV robot to go to in order to approach a dynamic target, and actions to take by the UAVs when the mobile UGV robot is obstructed and cannot reach the target. This method encourages the target and robot to work together more closely. This is one of the most difficult issues in search and rescue operations since human targets are seldom found using just land robots or aerial robots. Finally, the purpose of this thesis is to suggest that the evaluation of the performance of a collaborative robot system may be accomplished by measuring the mobility of robots. Even though multi-robot coordination aids in SAR opera- tions, the findings of the study presented in this thesis conclude that the integration of various autonomous robotic systems in unstructured environments is difficult and that there is currently no unitary analytical model that can be used for this purpose.

ContributorsCherupally, SuryaKiran (Author) / Redkar, Sangram (Thesis advisor) / Nichols, Kevin (Committee member) / Subramanian, Susheel Kumar Cherangara (Committee member) / Arizona State University (Publisher)

Created2022

Design and Development of an Autonomous Paramotor UAV

Description

This document is the culmination of research into small unmanned Powered Parachute aerial vehicles. This dissertation serves to provide designers of small systems with an approach to developing a Powered Parachute Unmanned Aerial Vehicle system, guiding them through the basic assumptions, dynamics, and control method. In addition, this dissertation aims…

This document is the culmination of research into small unmanned Powered Parachute aerial vehicles. This dissertation serves to provide designers of small systems with an approach to developing a Powered Parachute Unmanned Aerial Vehicle system, guiding them through the basic assumptions, dynamics, and control method. In addition, this dissertation aims to generate a reliable and generalized framework of dynamic design and control methods for autonomous Powered Parachute aircraft. The simulation methods in this paper assist in developing a consistent and robust unmanned system for applying Powered Parachutes as an alternative to multirotor or fixed-wing aircraft.The first chapter serves as a primer on the historical applications of small Unmanned Systems and Powered Parachutes and gives an overview of the requirements for building an autonomous Powered Parachutes; the information within this chapter provides justification background for the second chapter on Powered Parachute dynamics. In the dynamics chapter, equations of motion are derived using engineering first principles. This chapter also discusses alternative methods of improving the control and robustness of the Powered Parachute airframe. The dynamics model is used in all further chapters to develop a generalized control system to operate such a model autonomously. Chapter three of this document focuses on developing simulations from the dynamics described in the previous chapter, laying the groundwork for guidance, navigation, and control algorithms ahead. Chapters four and onwards refine the autonomous control of the Powered Parachute aircraft for real-world scenarios, discussing correction factors and minimizing the errors present in current sensor systems. Chapter five covers the development of an additional adaptive controller which uses a Sigma-Pi Neural network integrated into the final control loop. Chapter six develops advanced control methods for the Powered Parachute airframe, including simulations on a novel proposed thrust vectoring method. Finally, chapter seven discusses results accumulated from testing an experimental prototype.

ContributorsFiedler, Brett (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Phatak, Amar (Committee member) / Arizona State University (Publisher)

Created2022

Co-Bot Integration For High-Volume Manufacturing of Aerospace Components

Description

Over the years, American manufacturing has been offshored due to the competitive labor conditions in other countries. In addition, the COVID-19 pandemic exposed the fragility of the international supply chain, highlighting the importance of reshoring manufacturing and industry. However, reshoring alone cannot solve the underlying issues that caused offshoring in…

Over the years, American manufacturing has been offshored due to the competitive labor conditions in other countries. In addition, the COVID-19 pandemic exposed the fragility of the international supply chain, highlighting the importance of reshoring manufacturing and industry. However, reshoring alone cannot solve the underlying issues that caused offshoring in the first place, such as shortages of skilled labor and extensive regulation. To address these issues, the implementation and scaling of automation and Industry 4.0 technologies are necessary. The aerospace industry is a prime example of the need for skilled labor. Abiding by rigorous specifications and achieving the tight tolerances required by aerospace specifications is a highly specialized skill that requires experience and training. The shortage of skilled labor puts those working in aerospace at a disadvantage, often leading to long strenuous work hours to meet demand. To address this, a collaboration with two ASU manufacturing student research teams aided the development of two co-bot solutions that can work alongside technicians and operators to reduce downtime, increase efficiency, and free up human operators to focus on more complex tasks. While many automated solutions are available on the market, co-bots are not often used to their full capability. The proposed solutions demonstrate the possibilities of implementing co-bots in the aerospace industry by using them in machine tending and blending processes for aerospace parts. In traditional manufacturing processes, human operators are still responsible for performing repetitive and often mundane tasks, such as loading and removing workpieces from a CNC workstation and starting a CNC machine for repetitive parts. The current blending process requires a technician to manually sand damaged areas for Depot, Repair, and Overhaul (DRO), which is time-consuming and strenuous. By using a co-bot for this process, the technician's workload is significantly reduced, decreasing lead times and increasing quality control. Inspiration for this thesis came from observing the demands of companies like SpaceX, which require mass manufacturing of rocket engines to meet testing and launch schedules. The SpaceX Raptor engine is a complex, precise system that is aimed at being produced in high volume, which is a prime target for co-bot integration to help meet production targets. Implementing more co-bots into manufacturing has been shown to increase efficiency, reduce cost, and relieve stress on human operators. The integration of co-bots into the manufacturing process for the Raptor engine has the potential to improve efficiency and productivity, making high-volume manufacturing a possibility. Overall, the implementation of co-bots in the aerospace industry can offer a competitive advantage by increasing productivity and efficiency while reducing costs and relieving stress on human operators. This thesis provides proof of the possibilities of implementing co-bots in a versatile industry like aerospace and demonstrates the potential benefits of integrating co-bots into the manufacturing process for rocket engines like the Raptor. By doing so, the aerospace industry can move towards a more automated and efficient future, helping to address the challenges faced by American manufacturing today.

ContributorsMorse, Connor (Author) / Gintz, Jerry (Thesis director) / Hillary, Scott (Committee member) / Barrett, The Honors College (Contributor) / School of Manufacturing Systems and Networks (Contributor)

Created2023-05

Towards Energy-efficient Visual Navigation: Sensor Quantization and Event-based Vision Pipelines

Description

Visual navigation is a useful and important task for a variety of applications. As the prevalence of robots increase, there is an increasing need for energy-efficient navigation methods as well. Many aspects of efficient visual navigation algorithms have been implemented in the literature, but there is a lack of work…

Visual navigation is a useful and important task for a variety of applications. As the prevalence of robots increase, there is an increasing need for energy-efficient navigation methods as well. Many aspects of efficient visual navigation algorithms have been implemented in the literature, but there is a lack of work on evaluation of the efficiency of the image sensors. In this thesis, two methods are evaluated: adaptive image sensor quantization for traditional camera pipelines as well as new event-based sensors for low-power computer vision.The first contribution in this thesis is an evaluation of performing varying levels of sensor linear and logarithmic quantization with the task of visual simultaneous localization and mapping (SLAM). This unconventional method can provide efficiency benefits with a trade off between accuracy of the task and energy-efficiency. A new sensor quantization method, gradient-based quantization, is introduced to improve the accuracy of the task. This method only lowers the bit level of parts of the image that are less likely to be important in the SLAM algorithm since lower bit levels signify better energy-efficiency, but worse task accuracy. The third contribution is an evaluation of the efficiency and accuracy of event-based camera intensity representations for the task of optical flow. The results of performing a learning based optical flow are provided for each of five different reconstruction methods along with ablation studies. Lastly, the challenges of an event feature-based SLAM system are presented with results demonstrating the necessity for high quality and high resolution event data. The work in this thesis provides studies useful for examining tradeoffs for an efficient visual navigation system with traditional and event vision sensors. The results of this thesis also provide multiple directions for future work.

ContributorsChristie, Olivia Catherine (Author) / Jayasuriya, Suren (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)

Created2022

The Viability of Humanoid Robotics Utilizing the Kinetic Chain Approach, Assessed in the Optimization of a Thrown Disc

Description

The objective goal of this research is to maximize the speed of the end effector of a three link R-R-R mechanical system with constrained torque input control. The project utilizes MATLAB optimization tools to determine the optimal throwing motion of a simulated mechanical system, while mirroring the physical parameters and…

The objective goal of this research is to maximize the speed of the end effector of a three link R-R-R mechanical system with constrained torque input control. The project utilizes MATLAB optimization tools to determine the optimal throwing motion of a simulated mechanical system, while mirroring the physical parameters and constraints of a human arm wherever possible. The analysis of this final result determines if the kinetic chain effect is present in the theoretically optimized solution. This is done by comparing it with an intuitively optimized system based on throwing motion derived from the forehand throw in Ultimate frisbee.

ContributorsHartmann, Julien (Author) / Grewal, Anoop (Thesis director) / Redkar, Sangram (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)

Created2022-05

Robust Performance Monitoring for Adaptive PID Controllers in System Recovery from Insufficient Excitation

Description

The aim of this thesis is to study adaptive controllers in the context of a Pro-portional Integral Derivative (PID) controller. The PID controller is tuned via loop shaping techniques to ensure desired robustness and performance characteristics with respect to a target loop shape. There are two problems that this work…

The aim of this thesis is to study adaptive controllers in the context of a Pro-portional Integral Derivative (PID) controller. The PID controller is tuned via loop shaping techniques to ensure desired robustness and performance characteristics with respect to a target loop shape. There are two problems that this work addresses: Consider a system that is controlled via an adaptive PID controller. If in absence of or under lack of excitation, the system or controller parameters drift to an arbitrary system (that may or may not be stable). Then, once the system gets sufficient ex- citation, there are two questions to be addressed: First, how quickly is the system able to recover to the target system, and in the process of recovery, how large are the transient overshoots and what factors affect the recovery of the drifted system? Second, continuous online adaptation of the controller may not always be necessary (and economical). So, is there a means to monitor the performance of the current controller and determine via robustness conditions whether to continue with the same controller or reject it and adapt to a new controller? Hence, this work is concerned with robust performance monitoring and recovery of an adaptive PID control system that had drifted to another system in absence of sufficient excitation or excessive noise.

Contributorsiyer, kaushik (Author) / Tsakalis, Konstantinos (Thesis advisor) / Arenz, Christian (Committee member) / Redkar, Sangram (Committee member) / Arizona State University (Publisher)

Created2024

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