Matching Items (61)
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- All Subjects: robotics
- All Subjects: Biomechanics
- All Subjects: Rehabilitation
- Creators: Lee, Hyunglae
- Creators: Artemiadis, Panagiotis
- Member of: ASU Electronic Theses and Dissertations
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
Admittance control with fixed damping has been a successful control strategy in previous human-robotic interaction research. This research implements a variable damping admittance controller in a 7-DOF robotic arm coupled with a human subject’s arm at the end effector to study the trade-off of agility and stability and aims to produce a control scheme which displays both fast rise time and stability. The variable damping controller uses a measure of intent of movement to vary damping to aid the user’s movement to a target. The range of damping values is bounded by incorporating knowledge of a human arm to ensure the stability of the coupled human-robot system. Human subjects completed experiments with fixed positive, fixed negative, and variable damping controllers to evaluate the variable damping controller’s ability to increase agility and stability. Comparisons of the two fixed damping controllers showed as fixed damping increased, the coupled human-robot system reacted with less overshoot at the expense of rise time, which is used as a measure of agility. The inverse was also true; as damping became increasingly negative, the overshoot and stability of the system was compromised, while the rise time became faster. Analysis of the variable damping controller demonstrated humans could extract the benefits of the variable damping controller in its ability to increase agility in comparison to a positive damping controller and increase stability in comparison to a negative damping controller.
ContributorsBitz, Tanner Jacob (Author) / Lee, Hyunglae (Thesis advisor) / Marvi, Hamidreza (Committee member) / Yong, Sze Zheng (Committee member) / Arizona State University (Publisher)
Created2019
Description
This work presents the design, modeling, analysis, and experimental characterization and testing of soft wearable robotics for lower limb rehabilitation for the ankle and hip. The Soft Robotic Ankle-Foot Orthosis (SR-AFO) is a wearable soft robot designed using multiple pneumatically-powered soft actuators to assist the ankle in multiple degrees-of-freedom during standing and walking tasks. The flat fabric pneumatic artificial muscle (ff-PAM) contracts upon pressurization and assists ankle plantarflexion in the sagittal plane. The Multi-material Actuator for Variable Stiffness (MAVS) aids in supporting ankle inversion/eversion in the frontal plane. Analytical models of the ff-PAM and MAVS were created to understand how the changing of the design parameters affects tensile force generation and stiffness support, respectively. The models were validated by both finite element analysis and experimental characterization using a universal testing machine. A set of human experiments were performed with healthy participants: 1) to measure lateral ankle support during quiet standing, 2) to determine lateral ankle support during walking over compliant surfaces, and 3) to evaluate plantarflexion assistance at push-off during treadmill walking, and 4) determine if the SR-AFO could be used for gait entrainment. Group results revealed increased ankle stiffness during quiet standing with the MAVS active, reduced ankle deflection while walking over compliant surfaces with the MAVS active, and reduced muscle effort from the SOL and GAS during 40 - 60% of the gait cycle with the dual ff-PAM active. The SR-AFO shows promising results in providing lateral ankle support and plantarflexion assistance with healthy participants, and a drastically increased basin of entrainment, which suggests a capability to help restore the gait of impaired users in future trials. The ff-PAM actuators were used in an X-orientation to assist the hip in flexion and extension. The Soft Robotic Hip Exosuit (SR-HExo) was evaluated using the same set of actuators and trials with healthy participants showed reduction in muscle effort during hip flexion and extension to further enhance the study of soft fabric actuators on human gait assistance.
ContributorsThalman, Carly Megan (Author) / Lee, Hyunglae (Thesis advisor) / Artemiadis, Panagiotis (Thesis advisor) / Sugar, Thomas (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2021
Description
Tubes and pipelines serve as a major component of several units in power plants and oil, gas, and water transmission. These structures undergo extreme conditions, where temperature and pressure vary, leading to corroding of the pipe over time, creating defects in them. A small crack in these tubes can cause major safety problems, so a regular inspection of these tubes is required. Most power plants prefer to use non-destructive testing procedures, such as long-range ultrasonic testing and phased array ultrasonic testing, to name a few. These procedures can be carried out with the help of crawlers that go inside the pipes. One of the main drawbacks of the current robotic tube inspection robots is the lack of maneuverability over complex tubular structures and the inability to traverse non-ferromagnetic pipelines. The main motivation of this project is to create a robotic system that can grab onto ferromagnetic and non-ferromagnetic tubes and move along those, move onto adjacent tubes, and maneuver around flanges and bends in the tube. Furthermore, most of the robots used for inspection rely on roller balls and suction-based components that can allow the robot to hold on to the curved surface of the tube. These techniques fail when the surface is rough or uneven, which has served as an inspiration to look at friction-based solutions. Lizards are known for their agile locomotion, as well as their ability to grab on any surface irrespective of the surface texture. The work presented here is focused on the design and control of a lizard-inspired tube inspection robot that can be used to inspect complex tubular structures made of any material.
ContributorsMasurkar, Nihar Dattaram (Author) / Marvi, Hamidreza (Thesis advisor) / Dehghan-Niri, Ehsan (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2022
Description
As the explorations beyond the Earth's boundaries continue to evolve, researchers and engineers strive to develop versatile technologies capable of adapting to unknown space conditions. For instance, the utilization of Screw-Propelled Vehicles (SPVs) and robotics that utilize helical screws propulsion to transverse planetary bodies is a growing area of interest. An example of such technology is the Extant Exobiology Life Surveyor (EELS), a snake-like robot currently developed by the NASA Jet Propulsion Laboratory (JPL) to explore the surface of Saturn’s moon, Enceladus. However, the utilization of such a mechanism requires a deep and thorough understanding of screw mobility in uncertain conditions. The main approach to exploring screw dynamics and optimal design involves the utilization of Discrete Element Method (DEM) simulations to assess interactions and behavior of screws when interacting with granular terrains. In this investigation, the Simplified Johnson-Kendall-Roberts (SJKR) model is implemented into the utilized simulation environment to account for cohesion effects similar to what is experienced on celestial bodies like Enceladus. The model is verified and validated through experimental and theoretical testing. Subsequently, the performance characteristics of screws are explored under varying parameters, such as thread depth, number of screw starts, and the material’s cohesion level. The study has examined significant relationships between the parameters under investigation and their influence on the screw performance.
ContributorsAbdelrahim, Mohammad (Author) / Marvi, Hamid (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2023
Description
Soft robotics has garnered attention for its substantial prospective in various domains, such as manipulation and interactions with humans, by offering competitive advantages against rigid robotic systems, including inherent compliance and variable stiffness. Despite these benefits, their theoretically infinite degrees of freedom and prominent nonlinearities pose significant challenges in developing dynamic models and guiding the robots along desired paths. Additionally, soft robots may exhibit rigid behaviors and potentially collide with their surroundings during path tracking tasks, particularly when possible contact points are unknown. In this dissertation, reduced-order models are used to describe the behaviors of three different soft robot designs, including both linear parameter varying (LPV) and augmented rigid robot (ARR) models. While the reduced-order model captures the majority of the soft robot's dynamics, modeling uncertainties notably remain. Non-repeated modeling uncertainties are addressed by categorizing them as a lumped disturbance, employing two methodologies, $H_\infty$ method and nonlinear disturbance observer (NDOB) based sliding mode control, for its rejection. For repeated disturbances, an iterative learning control (ILC) with a P-type learning function is implemented to enhance trajectory tracking efficacy. Furthermore,for non-repeated disturbances, the NDOB facilitates the contact estimation, and its results are jointly used with a switching algorithm to modify the robot trajectories. The stability proof of all controllers and corresponding simulation and experimental results are provided. For a path tracking task of a soft robot with multi-segments, a robust control strategy that combines a LPV model with an innovative improved nonlinear disturbance observer-based adaptive sliding mode control (INASMC). The control framework employs a first-order LPV model for dynamic representation, leverages an improved disturbance observer for accurate disturbance forecasting, and utilizes adaptive sliding mode control to effectively counteract uncertainties. The tracking error under the proposed controller is proven to be asymptotically stable, and the controller's effectiveness is is validated with simulation and experimental results. Ultimately, this research mitigates the inherent uncertainty in soft robot modeling, thereby enhancing their functionality in contact-intensive tasks.
ContributorsQIAO, ZHI (Author) / Zhang, Wenlong (Thesis advisor) / Marvi, Hamidreza (Committee member) / Lee, Hyunglae (Committee member) / Berman, Spring (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2023
Description
While wearable soft robots have successfully addressed many inherent design limitations faced by wearable rigid robots, they possess a unique set of challenges due to their soft and compliant nature. Some of these challenges are present in the sensing, modeling, control and evaluation of wearable soft robots. Machine learning algorithms have shown promising results for sensor fusion with wearable robots, however, they require extensive data to train models for different users and experimental conditions. Modeling soft sensors and actuators require characterizing non-linearity and hysteresis, which complicates deriving an analytical model. Experimental characterization can capture the characteristics of non-linearity and hysteresis but requires developing a synthesized model for real-time control. Controllers for wearable soft robots must be robust to compensate for unknown disturbances that arise from the soft robot and its interaction with the user. Since developing dynamic models for soft robots is complex, inaccuracies that arise from the unmodeled dynamics lead to significant disturbances that the controller needs to compensate for. In addition, obtaining a physical model of the human-robot interaction is complex due to unknown human dynamics during walking. Finally, the performance of soft robots for wearable applications requires extensive experimental evaluation to analyze the benefits for the user. To address these challenges, this dissertation focuses on the sensing, modeling, control and evaluation of soft robots for wearable applications. A model-based sensor fusion algorithm is proposed to improve the estimation of human joint kinematics, with a soft flexible robot that requires compact and lightweight sensors. To overcome limitations with rigid sensors, an inflatable soft haptic sensor is developed to enable gait sensing and haptic feedback. Through experimental characterization, a mathematical model is derived to quantify the user's ground reaction forces and the delivered haptic force. Lastly, the performance of a wearable soft exosuit in assisting human users during lifting tasks is evaluated, and the benefits obtained from the soft robot assistance are analyzed.
ContributorsQuiñones Yumbla, Emiliano (Author) / Zhang, Wenlong (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2023
Description
One of the long-standing issues that has arisen in the sports medicine field is identifying the ideal methodology to optimize recovery following anterior cruciate ligament reconstruction (ACLR). The perioperative period for ACLR is notoriously heterogeneous in nature as it consists of many variables that can impact surgical outcomes. While there has been extensive literature published regarding the efficacy of various recovery and rehabilitation topics, it has been widely acknowledged that certain modalities within the field of ACLR rehabilitation need further high-quality evidence to support their use in clinical practice, such as blood flow restriction (BFR) training. BFR training involves the application of a tourniquet-like cuff to the proximal aspect of a limb prior to exercise; the cuff is inflated so that it occludes venous flow but allows arterial inflow. BFR is usually combined with low-intensity (LI) resistance training, with resistance as low as 20% of one-repetition maximum (1RM). LI-BFR has been used as an emerging clinical modality to combat postoperative atrophy of the quadriceps muscles for those who have undergone ACLR, as these individuals cannot safely tolerate high muscular tension exercise after surgery. Impairments of the quadriceps are the major cause of poor functional status of patients following an otherwise successful ACLR procedure; however, these impairments can be mitigated with preoperative rehabilitation done before surgery. It was hypothesized that the use of a preoperative LI-BFR training protocol could help improve postoperative outcomes following ACLR; primarily, strength and hypertrophy of the quadriceps. When compared with a SHAM control group, subjects who were randomized to a BFR intervention group made greater preoperative strength gains in the quadriceps and recovered quadriceps mass at an earlier timepoint than that of the SHAM group aftersurgery; however, the gains made in strength were not able to be maintained in the 8-week postoperative period. While these results do not support the use of LI-BFR from the short-term perspective after ACLR, follow-up data will be used to investigate trends in re-injury and return to sport rates to evaluate the efficacy of the use of LI-BFR from a long-term perspective.
ContributorsGlattke, Kaycee Elizabeth (Author) / Lockhart, Thurmon (Thesis advisor) / McDaniel, Troy (Committee member) / Banks, Scott (Committee member) / Peterson, Daniel (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2022