Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
Displaying 1 - 10 of 32
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- All Subjects: robotics
- Creators: Artemiadis, Panagiotis
Description
As robots are increasingly migrating out of factories and research laboratories and into our everyday lives, they should move and act in environments designed for humans. For this reason, the need of anthropomorphic movements is of utmost importance. The objective of this thesis is to solve the inverse kinematics problem of redundant robot arms that results to anthropomorphic configurations. The swivel angle of the elbow was used as a human arm motion parameter for the robot arm to mimic. The swivel angle is defined as the rotation angle of the plane defined by the upper and lower arm around a virtual axis that connects the shoulder and wrist joints. Using kinematic data recorded from human subjects during every-day life tasks, the linear sensorimotor transformation model was validated and used to estimate the swivel angle, given the desired end-effector position. Defining the desired swivel angle simplifies the kinematic redundancy of the robot arm. The proposed method was tested with an anthropomorphic redundant robot arm and the computed motion profiles were compared to the ones of the human subjects. This thesis shows that the method computes anthropomorphic configurations for the robot arm, even if the robot arm has different link lengths than the human arm and starts its motion at random configurations.
ContributorsWang, Yuting (Author) / Artemiadis, Panagiotis (Thesis advisor) / Mignolet, Marc (Committee member) / Santos, Veronica J (Committee member) / Arizona State University (Publisher)
Created2013
Description
Electromyogram (EMG)-based control interfaces are increasingly used in robot teleoperation, prosthetic devices control and also in controlling robotic exoskeletons. Over the last two decades researchers have come up with a plethora of decoding functions to map myoelectric signals to robot motions. However, this requires a lot of training and validation data sets, while the parameters of the decoding function are specific for each subject. In this thesis we propose a new methodology that doesn't require training and is not user-specific. The main idea is to supplement the decoding functional error with the human ability to learn inverse model of an arbitrary mapping function. We have shown that the subjects gradually learned the control strategy and their learning rates improved. We also worked on identifying an optimized control scheme that would be even more effective and easy to learn for the subjects. Optimization was done by taking into account that muscles act in synergies while performing a motion task. The low-dimensional representation of the neural activity was used to control a two-dimensional task. Results showed that in the case of reduced dimensionality mapping, the subjects were able to learn to control the device in a slower pace, however they were able to reach and retain the same level of controllability. To summarize, we were able to build an EMG-based controller for robot devices that would work for any subject, without any training or decoding function, suggesting human-embedded controllers for robotic devices.
ContributorsAntuvan, Chris Wilson (Author) / Artemiadis, Panagiotis (Thesis advisor) / Muthuswamy, Jitendran (Committee member) / Santos, Veronica J (Committee member) / Arizona State University (Publisher)
Created2013
Description
Humans have an inherent capability of performing highly dexterous and skillful tasks with their arms, involving maintaining posture, movement and interacting with the environment. The latter requires for them to control the dynamic characteristics of the upper limb musculoskeletal system. Inertia, damping and stiffness, a measure of mechanical impedance, gives a strong representation of these characteristics. Many previous studies have shown that the arm posture is a dominant factor for determining the end point impedance in a horizontal plane (transverse plane). The objective of this thesis is to characterize end point impedance of the human arm in the three dimensional (3D) space. Moreover, it investigates and models the control of the arm impedance due to increasing levels of muscle co-contraction. The characterization is done through experimental trials where human subjects maintained arm posture, while perturbed by a robot arm. Moreover, the subjects were asked to control the level of their arm muscles' co-contraction, using visual feedback of their muscles' activation, in order to investigate the effect of the muscle co-contraction on the arm impedance. The results of this study showed a very interesting, anisotropic increase of the arm stiffness due to muscle co-contraction. This can lead to very useful conclusions about the arm biomechanics as well as many implications for human motor control and more specifically the control of arm impedance through muscle co-contraction. The study finds implications for the EMG-based control of robots that physically interact with humans.
ContributorsPatel, Harshil Naresh (Author) / Artemiadis, Panagiotis (Thesis advisor) / Berman, Spring (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
As robots become more prevalent, the need is growing for efficient yet stable control systems for applications with humans in the loop. As such, it is a challenge for scientists and engineers to develop robust and agile systems that are capable of detecting instability in teleoperated systems. Despite how much research has been done to characterize the spatiotemporal parameters of human arm motions for reaching and gasping, not much has been done to characterize the behavior of human arm motion in response to control errors in a system. The scope of this investigation is to investigate human corrective actions in response to error in an anthropomorphic teleoperated robot limb. Characterizing human corrective actions contributes to the development of control strategies that are capable of mitigating potential instabilities inherent in human-machine control interfaces. Characterization of human corrective actions requires the simulation of a teleoperated anthropomorphic armature and the comparison of a human subject's arm kinematics, in response to error, against the human arm kinematics without error. This was achieved using OpenGL software to simulate a teleoperated robot arm and an NDI motion tracking system to acquire the subject's arm position and orientation. Error was intermittently and programmatically introduced to the virtual robot's joints as the subject attempted to reach for several targets located around the arm. The comparison of error free human arm kinematics to error prone human arm kinematics revealed an addition of a bell shaped velocity peak into the human subject's tangential velocity profile. The size, extent, and location of the additional velocity peak depended on target location and join angle error. Some joint angle and target location combinations do not produce an additional peak but simply maintain the end effector velocity at a low value until the target is reached. Additional joint angle error parameters and degrees of freedom are needed to continue this investigation.
ContributorsBevilacqua, Vincent Frank (Author) / Artemiadis, Panagiotis (Thesis director) / Santello, Marco (Committee member) / Trimble, Steven (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2013-05
Description
I worked on the human-machine interface to improve human physical capability. This work was done in the Human Oriented Robotics and Control Lab (HORC) towards the creation of an advanced, EMG-controlled exoskeleton. The project was new, and any work on the human- machine interface needs the physical interface itself. So I designed and fabricated a human-robot coupling device with a novel safety feature. The validation testing of this coupling proved very successful, and the device was granted a provisional patent as well as published to facilitate its spread to other human-machine interface applications, where it could be of major benefit. I then employed this coupling in experimentation towards understanding impedance, with the end goal being the creation of an EMG-based impedance exoskeleton control system. I modified a previously established robot-to-human perturbation method for use in my novel, three- dimensional (3D) impedance measurement experiment. Upon execution of this experiment, I was able to successfully characterize passive, static human arm stiffness in 3D, and in doing so validated the aforementioned method. This establishes an important foundation for promising future work on understanding impedance and the creation of the proposed control scheme, thereby furthering the field of human-robot interaction.
ContributorsO'Neill, Gerald D. (Author) / Artemiadis, Panagiotis (Thesis director) / Santello, Marco (Committee member) / Santos, Veronica (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2013-05
Description
This thesis focused on grasping tasks with the goal of investigating, analyzing, and quantifying human catching trends by way of a mathematical model. The aim of this project was to study human trends in a dynamic grasping task (catching a rolling ball), relate those discovered trends to kinematic characteristics of the object, and use this relation to control a robot hand in real time. As an ultimate goal, it was hoped that this research will aide in furthering the bio-inspiration in robot control methods. To achieve the above goal, firstly a tactile sensing glove was developed. This instrument allowed for in depth study of human reactionary grasping movements when worn by subjects during experimentation. This sensing glove system recorded force data from the palm and motion data from four fingers. From these data sets, temporal trends were established relating to when subjects initiated grasping during each trial. Moreover, optical tracking was implemented to study the kinematics of the moving object during human experiments and also to close the loop during the control of the robot hand. Ultimately, a mathematical bio-inspired model was created. This was embodied in a two-term decreasing power function which related the temporal trend of wait time to the ball initial acceleration. The wait time is defined as the time between when the experimental conductor releases the ball and when the subject begins to initiate grasping by closing their fingers, over a distance of four feet. The initial acceleration is the first acceleration value of the object due to the force provided when the conductor throws the object. The distance over which the ball was thrown was incorporated into the model. This is discussed in depth within the thesis. Overall, the results presented here show promise for bio-inspired control schemes in the successful application of robotic devices. This control methodology will ideally be developed to move robotic prosthesis past discrete tasks and into more complicated activities.
ContributorsCard, Dillon (Co-author) / Mincieli, Jennifer (Co-author) / Artemiadis, Panagiotis (Thesis director) / Santos, Veronica (Committee member) / Middleton, James (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / W. P. Carey School of Business (Contributor)
Created2014-05
Description
This thesis focused on understanding how humans visually perceive swarm behavior through the use of swarm simulations and gaze tracking. The goal of this project was to determine visual patterns subjects display while observing and supervising a swarm as well as determine what swarm characteristics affect these patterns. As an ultimate goal, it was hoped that this research will contribute to optimizing human-swarm interaction for the design of human supervisory controllers for swarms. To achieve the stated goals, two investigations were conducted. First, subjects gaze was tracked while observing a simulated swarm as it moved across the screen. This swarm changed in size, disturbance level in the position of the agents, speed, and path curvature. Second, subjects were asked to play a supervisory role as they watched a swarm move across the screen toward targets. The subjects determined whether a collision would occur and with which target while their responses as well as their gaze was tracked. In the case of an observatory role, a model of human gaze was created. This was embodied in a second order model similar to that of a spring-mass-damper system. This model was similar across subjects and stable. In the case of a supervisory role, inherent weaknesses in human perception were found, such as the inability to predict future position of curved paths. These findings are discussed in depth within the thesis. Overall, the results presented suggest that understanding human perception of swarms offers a new approach to the problem of swarm control. The ability to adapt controls to the strengths and weaknesses could lead to great strides in the reduction of operators in the control of one UAV, resulting in a move towards one man operation of a swarm.
ContributorsWhitton, Elena Michelle (Author) / Artemiadis, Panagiotis (Thesis director) / Berman, Spring (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2015-05
Description
The focus of this project investigates high mobility robotics by developing a fully integrated framework for a ball-balancing robot. Using Lagrangian mechanics, a model for the robot was derived and used to conduct trade studies on significant system parameters. With a broad understanding of system dynamics, controllers were designed using LQR methodology. A prototype was then built and tested to exhibit desired reference command following and disturbance attenuation.
ContributorsKapron, Mark Andrew (Author) / Rodriguez, Armando (Thesis director) / Artemiadis, Panagiotis (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
A heterogeneous team of robots working in symbiosis can maximize their strengths while complementing each other’s weaknesses. These simple robots can achieve more working together than they could on their own but cost less than a single robot with the same combination of capabilities. This project aims to validate the symbiotic relationship of an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV) with a physical implementation of a heterogenous team of robots and a demonstration of their capabilities. This paper details the selection of robots, the design of the physical coupling mechanism, and the design of the autonomous controls. An experiment was performed to assess the capabilities of the robots according to four performance criteria. The UGV must navigate a space while the UAV follows. The UAV must couple with the UGV. The UAV must lift the UGV over an obstacle. The UGV must navigate the space while carrying the UAV.
ContributorsBreaux, Chris (Author) / Artemiadis, Panagiotis (Thesis director) / Lee, Hyunglae (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
This study presents quantification of ankle stability as affected by environmental conditions in two degrees of freedom (DOF) with three distinct analysis techniques. Additionally, this study presents gender-specific trends for comparison. Intuitively, ankle stability decreased in less stable environments with a negative simulated stiffness. Female subjects generally suffered a greater loss of stability in moderately and highly unstable environments. Both gender groups exhibited greater stability in the sagittal plane than the frontal plane across the entire range of simulated stiffness's. Outcomes of this study are useful in the design of controllers for lower extremity physically-interactive robotics, understanding situations in which the ankle is likely to lose stability, and understanding the strengths and weaknesses of unique analysis techniques.
ContributorsHanzlick, Harrison Patrick (Author) / Lee, Hyunglae (Thesis director) / Artemiadis, Panagiotis (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12