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- All Subjects: robotics
- Creators: Redkar, Sangram
- Creators: Aukes, Daniel
Description
Multi-material manufacturing combines multiple fabrication processes to produce individual parts that can be made up of several different materials. These processes can include both additive and subtractive manufacturing methods as well as embedding other components during manufacturing. This yields opportunities for creating single parts that can take the place of an assembly of parts produced using conventional techniques. Some example applications of multi-material manufacturing include parts that are produced using one process then machined to tolerance using another, parts with integrated flexible joints, or parts that contain discrete embedded components such as reinforcing materials or electronics.
Multi-material manufacturing has applications in robotics because, with it, mechanisms can be built into a design without adding additional moving parts. This allows for robot designs that are both robust and low cost, making it a particularly attractive method for education or research. 3D printing is of particular interest in this area because it is low cost, readily available, and capable of easily producing complicated part geometries. Some machines are also capable of depositing multiple materials during a single process. However, up to this point, planning the steps to create a part using multi-material manufacturing has been done manually, requiring specialized knowledge of the tools used. The difficulty of this planning procedure can prevent many students and researchers from using multi-material manufacturing.
This project studied methods of automating the planning of multi-material manufacturing processes through the development of a computational framework for processing 3D models and automatically generating viable manufacturing sequences. This framework includes solid operations and algorithms which assist the designer in computing manufacturing steps for multi-material models. This research is informing the development of a software planning tool which will simplify the planning needed by multi-material fabrication, making it more accessible for use in education or research.
In our paper, Voxel-Based Cad Framework for Planning Functionally Graded and Multi-Step Rapid Fabrication Processes, we present a new framework for representing and computing functionally-graded materials for use in rapid prototyping applications. We introduce the material description itself, low-level operations which can be used to combine one or more geometries together, and algorithms which assist the designer in computing manufacturing-compatible sequences. We then apply these techniques to several example scenarios. First, we demonstrate the use of a Gaussian blur to add graded material transitions to a model which can then be produced using a multi-material 3D printing process. Our second example highlights our solution to the problem of inserting a discrete, off-the-shelf part into a 3D printed model during the printing sequence. Finally, we implement this second example and manufacture two example components.
Multi-material manufacturing has applications in robotics because, with it, mechanisms can be built into a design without adding additional moving parts. This allows for robot designs that are both robust and low cost, making it a particularly attractive method for education or research. 3D printing is of particular interest in this area because it is low cost, readily available, and capable of easily producing complicated part geometries. Some machines are also capable of depositing multiple materials during a single process. However, up to this point, planning the steps to create a part using multi-material manufacturing has been done manually, requiring specialized knowledge of the tools used. The difficulty of this planning procedure can prevent many students and researchers from using multi-material manufacturing.
This project studied methods of automating the planning of multi-material manufacturing processes through the development of a computational framework for processing 3D models and automatically generating viable manufacturing sequences. This framework includes solid operations and algorithms which assist the designer in computing manufacturing steps for multi-material models. This research is informing the development of a software planning tool which will simplify the planning needed by multi-material fabrication, making it more accessible for use in education or research.
In our paper, Voxel-Based Cad Framework for Planning Functionally Graded and Multi-Step Rapid Fabrication Processes, we present a new framework for representing and computing functionally-graded materials for use in rapid prototyping applications. We introduce the material description itself, low-level operations which can be used to combine one or more geometries together, and algorithms which assist the designer in computing manufacturing-compatible sequences. We then apply these techniques to several example scenarios. First, we demonstrate the use of a Gaussian blur to add graded material transitions to a model which can then be produced using a multi-material 3D printing process. Our second example highlights our solution to the problem of inserting a discrete, off-the-shelf part into a 3D printed model during the printing sequence. Finally, we implement this second example and manufacture two example components.
ContributorsBrauer, Cole D (Author) / Aukes, Daniel (Thesis director) / Sodemann, Angela (Committee member) / Engineering Programs (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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 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
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 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
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 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
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 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
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 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
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 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
Description
Soft robots currently rely on additional hardware such as pumps, high voltage supplies,light generation sources, and magnetic field generators for their operation. These components
resist miniaturization; thus, embedding them into small-scale soft robots is challenging.
This issue limits their applications, especially in hyper-redundant mobile robots. This
dissertation aims at addressing some of the challenges associated with creating miniature,
untethered soft robots that can function without any attachment to external power supplies
or receiving any control signals from outside sources. This goal is accomplished by introducing
a soft active material and a manufacturing method that together, facilitate the
miniaturization of soft robots and effectively supports their autonomous, mobile operation
without any connection to outside equipment or human intervention.
The soft active material presented here is a hydrogel based on a polymer called poly(Nisopropylacrylamide)
(PNIPAAm). This hydrogel responds to changes in the temperature
and responds by expanding or contracting. A major challenge regarding PNIPAAm-based
hydrogels is their slow response. This challenge is addressed by introducing a mixedsolvent
photo-polymerization technique that alters the pore structure of the hydrogel and
facilitates the water transport and thus the rate of volume change. Using this technique,
the re-swelling response time of hydrogels is reduced to 2:4min – over 25 times faster
than hydrogels demonstrated previously. The material properties of hydrogels including
their response rate and Young’s modulus are tuned simultaneously. The one-step photopolymerization
using UV light is performed in under 15 sec, which is a significant improvement
over thermo-polymerization, which takes anywhere between a few minutes to
several hours. Photopolymerization is key towards simplifying recipes, improving access
to these techniques, and making them tractable for iterative design processes.
To address the manufacturing challenges, soft voxel actuators (SVAs) are presented.
SVAs are actuated by electrical currents through Joule heating. SVAs weighing only 100 mg require small footprint microcontrollers for their operation which can be embedded
in the robotic system. The advantages of hydrogel-based SVAs are demonstrated through
different robotic platforms namely a hyper-redundant manipulator with 16 SVAs, an untethered
miniature robot for mobile underwater applications using 8 SVAs, and a gripper
using 32 SVAs.
ContributorsKhodambashi, Roozbeh (Author) / Aukes, Daniel (Thesis advisor) / Sugar, Thomas (Committee member) / Nam, Changho (Committee member) / Arizona State University (Publisher)
Created2021
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 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
Description
In nature, some animals have an exoskeleton that provides protection, strength, and stability to the organism, but in engineering, an exoskeleton refers to a device that augments or aids human ability. However, the method of controlling these devices has been a challenge historically. Depending on the objective, control systems for exoskeletons have ranged from devices as simple spring-loaded systems to using sensors such as electromyography (EMG). Despite EMGs being very common, force sensing resistors (FSRs) can be used instead. There are multiple types of exoskeletons that target different areas of the human body, and the targeted area depends on the need of the device. Usually, the devices are developed for either medical or military usage; for this project, the focus is on medical development of an automated elbow joint to assist in rehabilitation. This thesis is a continuation of my ASU Barrett honors thesis, Upper-Extremity Exoskeleton. While working on my honors thesis, I helped develop a design for an upper extremity exoskeleton based on the Wilmer orthosis design for Mayo Clinic. Building upon the design of an orthosis, for the master’s thesis, I developed an FSR control system that is designed using a Wheatstone bridge circuit that can provide a clean reliable signal as compared to the current EMG setup.
ContributorsCarlton, Bryan (Author) / Sugar, Thomas (Thesis advisor) / Aukes, Daniel (Committee member) / Hollander, Kevin (Committee member) / Arizona State University (Publisher)
Created2023