Matching Items (37)
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- All Subjects: Mechanical Engineering
- Creators: Lee, Hyunglae
Description
The development of advanced, anthropomorphic artificial hands aims to provide upper extremity amputees with improved functionality for activities of daily living. However, many state-of-the-art hands have a large number of degrees of freedom that can be challenging to control in an intuitive manner. Automated grip responses could be built into artificial hands in order to enhance grasp stability and reduce the cognitive burden on the user. To this end, three studies were conducted to understand how human hands respond, passively and actively, to unexpected perturbations of a grasped object along and about different axes relative to the hand. The first study investigated the effect of magnitude, direction, and axis of rotation on precision grip responses to unexpected rotational perturbations of a grasped object. A robust "catch-up response" (a rapid, pulse-like increase in grip force rate previously reported only for translational perturbations) was observed whose strength scaled with the axis of rotation. Using two haptic robots, we then investigated the effects of grip surface friction, axis, and direction of perturbation on precision grip responses for unexpected translational and rotational perturbations for three different hand-centric axes. A robust catch-up response was observed for all axes and directions for both translational and rotational perturbations. Grip surface friction had no effect on the stereotypical catch-up response. Finally, we characterized the passive properties of the precision grip-object system via robot-imposed impulse perturbations. The hand-centric axis associated with the greatest translational stiffness was different than that for rotational stiffness. This work expands our understanding of the passive and active features of precision grip, a hallmark of human dexterous manipulation. Biological insights such as these could be used to enhance the functionality of artificial hands and the quality of life for upper extremity amputees.
ContributorsDe Gregorio, Michael (Author) / Santos, Veronica J. (Thesis advisor) / Artemiadis, Panagiotis K. (Committee member) / Santello, Marco (Committee member) / Sugar, Thomas (Committee member) / Helms Tillery, Stephen I. (Committee member) / Arizona State University (Publisher)
Created2013
Description
As robotic systems are used in increasingly diverse applications, the interaction of humans and robots has become an important area of research. In many of the applications of physical human robot interaction (pHRI), the robot and the human can be seen as cooperating to complete a task with some object of interest. Often these applications are in unstructured environments where many paths can accomplish the goal. This creates a need for the ability to communicate a preferred direction of motion between both participants in order to move in coordinated way. This communication method should be bidirectional to be able to fully utilize both the robot and human capabilities. Moreover, often in cooperative tasks between two humans, one human will operate as the leader of the task and the other as the follower. These roles may switch during the task as needed. The need for communication extends into this area of leader-follower switching. Furthermore, not only is there a need to communicate the desire to switch roles but also to control this switching process. Impedance control has been used as a way of dealing with some of the complexities of pHRI. For this investigation, it was examined if impedance control can be utilized as a way of communicating a preferred direction between humans and robots. The first set of experiments tested to see if a human could detect a preferred direction of a robot by grasping and moving an object coupled to the robot. The second set tested the reverse case if the robot could detect the preferred direction of the human. The ability to detect the preferred direction was shown to be up to 99% effective. Using these results, a control method to allow a human and robot to switch leader and follower roles during a cooperative task was implemented and tested. This method proved successful 84% of the time. This control method was refined using adaptive control resulting in lower interaction forces and a success rate of 95%.
ContributorsWhitsell, Bryan (Author) / Artemiadis, Panagiotis (Thesis advisor) / Santello, Marco (Committee member) / Santos, Veronica (Committee member) / Arizona State University (Publisher)
Created2014
Description
Learning by trial-and-error requires retrospective information that whether a past action resulted in a rewarded outcome. Previous outcome in turn may provide information to guide future behavioral adjustment. But the specific contribution of this information to learning a task and the neural representations during the trial-and-error learning process is not well understood. In this dissertation, such learning is analyzed by means of single unit neural recordings in the rats' motor agranular medial (AGm) and agranular lateral (AGl) while the rats learned to perform a directional choice task. Multichannel chronic recordings using implanted microelectrodes in the rat's brain were essential to this study. Also for fundamental scientific investigations in general and for some applications such as brain machine interface, the recorded neural waveforms need to be analyzed first to identify neural action potentials as basic computing units. Prior to analyzing and modeling the recorded neural signals, this dissertation proposes an advanced spike sorting system, the M-Sorter, to extract the action potentials from raw neural waveforms. The M-Sorter shows better or comparable performance compared with two other popular spike sorters under automatic mode. With the sorted action potentials in place, neuronal activity in the AGm and AGl areas in rats during learning of a directional choice task is examined. Systematic analyses suggest that rat's neural activity in AGm and AGl was modulated by previous trial outcomes during learning. Single unit based neural dynamics during task learning are described in detail in the dissertation. Furthermore, the differences in neural modulation between fast and slow learning rats were compared. The results show that the level of neural modulation of previous trial outcome is different in fast and slow learning rats which may in turn suggest an important role of previous trial outcome encoding in learning.
ContributorsYuan, Yu'an (Author) / Si, Jennie (Thesis advisor) / Buneo, Christopher (Committee member) / Santello, Marco (Committee member) / Chae, Junseok (Committee member) / Arizona State University (Publisher)
Created2014
Description
Animals learn to choose a proper action among alternatives according to the circumstance. Through trial-and-error, animals improve their odds by making correct association between their behavioral choices and external stimuli. While there has been an extensive literature on the theory of learning, it is still unclear how individual neurons and a neural network adapt as learning progresses. In this dissertation, single units in the medial and lateral agranular (AGm and AGl) cortices were recorded as rats learned a directional choice task. The task required the rat to make a left/right side lever press if a light cue appeared on the left/right side of the interface panel. Behavior analysis showed that rat's movement parameters during performance of directional choices became stereotyped very quickly (2-3 days) while learning to solve the directional choice problem took weeks to occur. The entire learning process was further broken down to 3 stages, each having similar number of recording sessions (days). Single unit based firing rate analysis revealed that 1) directional rate modulation was observed in both cortices; 2) the averaged mean rate between left and right trials in the neural ensemble each day did not change significantly among the three learning stages; 3) the rate difference between left and right trials of the ensemble did not change significantly either. Besides, for either left or right trials, the trial-to-trial firing variability of single neurons did not change significantly over the three stages. To explore the spatiotemporal neural pattern of the recorded ensemble, support vector machines (SVMs) were constructed each day to decode the direction of choice in single trials. Improved classification accuracy indicated enhanced discriminability between neural patterns of left and right choices as learning progressed. When using a restricted Boltzmann machine (RBM) model to extract features from neural activity patterns, results further supported the idea that neural firing patterns adapted during the three learning stages to facilitate the neural codes of directional choices. Put together, these findings suggest a spatiotemporal neural coding scheme in a rat AGl and AGm neural ensemble that may be responsible for and contributing to learning the directional choice task.
ContributorsMao, Hongwei (Author) / Si, Jennie (Thesis advisor) / Buneo, Christopher (Committee member) / Cao, Yu (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2014
Description
Effective tactile sensing in prosthetic and robotic hands is crucial for improving the functionality of such hands and enhancing the user's experience. Thus, improving the range of tactile sensing capabilities is essential for developing versatile artificial hands. Multimodal tactile sensors called BioTacs, which include a hydrophone and a force electrode array, were used to understand how grip force, contact angle, object texture, and slip direction may be encoded in the sensor data. Findings show that slip induced under conditions of high contact angles and grip forces resulted in significant changes in both AC and DC pressure magnitude and rate of change in pressure. Slip induced under conditions of low contact angles and grip forces resulted in significant changes in the rate of change in electrode impedance. Slip in the distal direction of a precision grip caused significant changes in pressure magnitude and rate of change in pressure, while slip in the radial direction of the wrist caused significant changes in the rate of change in electrode impedance. A strong relationship was established between slip direction and the rate of change in ratios of electrode impedance for radial and ulnar slip relative to the wrist. Consequently, establishing multiple thresholds or establishing a multivariate model may be a useful method for detecting and characterizing slip. Detecting slip for low contact angles could be done by monitoring electrode data, while detecting slip for high contact angles could be done by monitoring pressure data. Predicting slip in the distal direction could be done by monitoring pressure data, while predicting slip in the radial and ulnar directions could be done by monitoring electrode data.
ContributorsHsia, Albert (Author) / Santos, Veronica J (Thesis advisor) / Santello, Marco (Committee member) / Helms Tillery, Stephen I (Committee member) / Arizona State University (Publisher)
Created2012
Description
The interaction between humans and robots has become an important area of research as the diversity of robotic applications has grown. The cooperation of a human and robot to achieve a goal is an important area within the physical human-robot interaction (pHRI) field. The expansion of this field is toward moving robotics into applications in unstructured environments. When humans cooperate with each other, often there are leader and follower roles. These roles may change during the task. This creates a need for the robotic system to be able to exchange roles with the human during a cooperative task. The unstructured nature of the new applications in the field creates a need for robotic systems to be able to interact in six degrees of freedom (DOF). Moreover, in these unstructured environments, the robotic system will have incomplete information. This means that it will sometimes perform an incorrect action and control methods need to be able to correct for this. However, the most compelling applications for robotics are where they have capabilities that the human does not, which also creates the need for robotic systems to be able to correct human action when it detects an error. Activity in the brain precedes human action. Utilizing this activity in the brain can classify the type of interaction desired by the human. For this dissertation, the cooperation between humans and robots is improved in two main areas. First, the ability for electroencephalogram (EEG) to determine the desired cooperation role with a human is demonstrated with a correct classification rate of 65%. Second, a robotic controller is developed to allow the human and robot to cooperate in six DOF with asymmetric role exchange. This system allowed human-robot cooperation to perform a cooperative task at 100% correct rate. High, medium, and low levels of robotic automation are shown to affect performance, with the human making the greatest numbers of errors when the robotic system has a medium level of automation.
ContributorsWhitsell, Bryan Douglas (Author) / Artemiadis, Panagiotis (Thesis advisor) / Santello, Marco (Committee member) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Polygerinos, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2017
Description
Basilisk lizards are often studied for their unique ability to run across the surface of
water. Due to the complicated fluid dynamics of this process, the forces applied on the
water’s surface cannot be measured using traditional methods. This thesis presents a
novel technique of measuring the forces using a fluid dynamic force platform (FDFP),
a light, rigid box immersed in water. This platform, along with a motion capture
system, can be used to characterize the kinematics and dynamics of a basilisk lizard
running on water. This could ultimately lead to robots that can run on water in a
similar manner.
water. Due to the complicated fluid dynamics of this process, the forces applied on the
water’s surface cannot be measured using traditional methods. This thesis presents a
novel technique of measuring the forces using a fluid dynamic force platform (FDFP),
a light, rigid box immersed in water. This platform, along with a motion capture
system, can be used to characterize the kinematics and dynamics of a basilisk lizard
running on water. This could ultimately lead to robots that can run on water in a
similar manner.
ContributorsSweeney, Andrew Joseph (Author) / Marvi, Hamidreza (Thesis advisor) / Lentink, David (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2019
Description
Soft Poly-Limb (SPL) is a pneumatically driven, wearable, soft continuum robotic arm designed to aid humans with medical conditions, such as cerebral palsy, paraplegia, cervical spondylotic myelopathy, perform activities of daily living. To support user's tasks, the SPL acts as an additional limb extending from the human body which can be controlled to perform safe and compliant mobile manipulation in three-dimensional space. The SPL is inspired by invertebrate limbs, such as the elephant trunk and the arms of the octopus. In this work, various geometrical and physical parameters of the SPL are identified, and behavior of the actuators that comprise it are studied by varying their parameters through novel quasi-static computational models. As a result, this study provides a set of engineering design rules to create soft actuators for continuum soft robotic arms by understanding how varying parameters affect the actuator's motion as a function of the input pressure. A prototype of the SPL is fabricated to analyze the accuracy of these computational models by performing linear expansion, bending and arbitrary pose tests. Furthermore, combinations of the parameters based on the application of the SPL are determined to affect the weight, payload capacity, and stiffness of the arm. Experimental results demonstrate the accuracy of the proposed computational models and help in understanding the behavior of soft compliant actuators. Finally, based on the set functional requirements for the assistance of impaired users, results show the effectiveness of the SPL in performing tasks for activities of daily living.
ContributorsNuthi, Sai Gautham (Author) / Polygerinos, Panagiotis (Thesis advisor) / Lee, Hyunglae (Committee member) / Yong, Sze Zheng (Committee member) / Arizona State University (Publisher)
Created2018
Description
The world population is aging. Age-related disorders such as stroke and spinal cord injury are increasing rapidly, and such patients often suffer from mobility impairment. Wearable robotic exoskeletons are developed that serve as rehabilitation devices for these patients. In this thesis, a knee exoskeleton design with higher torque output compared to the first version, is designed and fabricated.
A series elastic actuator is one of the many actuation mechanisms employed in exoskeletons. In this mechanism a torsion spring is used between the actuator and human joint. It serves as torque sensor and energy buffer, making it compact and
safe.
A version of knee exoskeleton was developed using the SEA mechanism. It uses worm gear and spur gear combination to amplify the assistive torque generated from the DC motor. It weighs 1.57 kg and provides a maximum assistive torque of 11.26 N·m. It can be used as a rehabilitation device for patients affected with knee joint impairment.
A new version of exoskeleton design is proposed as an improvement over the first version. It consists of components such as brushless DC motor and planetary gear that are selected to meet the design requirements and biomechanical considerations. All the other components such as bevel gear and torsion spring are selected to be compatible with the exoskeleton. The frame of the exoskeleton is modeled in SolidWorks to be modular and easy to assemble. It is fabricated using sheet metal aluminum. It is designed to provide a maximum assistive torque of 23 N·m, two times over the present exoskeleton. A simple brace is 3D printed, making it easy to wear and use. It weighs 2.4 kg.
The exoskeleton is equipped with encoders that are used to measure spring deflection and motor angle. They act as sensors for precise control of the exoskeleton.
An impedance-based control is implemented using NI MyRIO, a FPGA based controller. The motor is controlled using a motor driver and powered using an external battery source. The bench tests and walking tests are presented. The new version of exoskeleton is compared with first version and state of the art devices.
A series elastic actuator is one of the many actuation mechanisms employed in exoskeletons. In this mechanism a torsion spring is used between the actuator and human joint. It serves as torque sensor and energy buffer, making it compact and
safe.
A version of knee exoskeleton was developed using the SEA mechanism. It uses worm gear and spur gear combination to amplify the assistive torque generated from the DC motor. It weighs 1.57 kg and provides a maximum assistive torque of 11.26 N·m. It can be used as a rehabilitation device for patients affected with knee joint impairment.
A new version of exoskeleton design is proposed as an improvement over the first version. It consists of components such as brushless DC motor and planetary gear that are selected to meet the design requirements and biomechanical considerations. All the other components such as bevel gear and torsion spring are selected to be compatible with the exoskeleton. The frame of the exoskeleton is modeled in SolidWorks to be modular and easy to assemble. It is fabricated using sheet metal aluminum. It is designed to provide a maximum assistive torque of 23 N·m, two times over the present exoskeleton. A simple brace is 3D printed, making it easy to wear and use. It weighs 2.4 kg.
The exoskeleton is equipped with encoders that are used to measure spring deflection and motor angle. They act as sensors for precise control of the exoskeleton.
An impedance-based control is implemented using NI MyRIO, a FPGA based controller. The motor is controlled using a motor driver and powered using an external battery source. The bench tests and walking tests are presented. The new version of exoskeleton is compared with first version and state of the art devices.
ContributorsJhawar, Vaibhav (Author) / Zhang, Wenlong (Thesis advisor) / Sugar, Thomas G. (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2018
Description
The Basilisk lizard is known for its agile locomotion capabilities on granular and aquatic media making it an impressive model organism for studying multi-terrain locomotion mechanics. The work presented here is aimed at understanding locomotion characteristics of Basilisk lizards through a systematic series of robotic and animal experiments. In this work, a Basilisk lizard inspired legged robot with bipedal and quadrupedal locomotion capabilities is presented. A series of robot experiments are conducted on dry and wet (saturated) granular media to determine the effects of gait parameters and substrate saturation, on robot velocity and energetics. Gait parameters studied here are stride frequency and stride length. Results of robot experiments are compared with previously obtained animal data. It is observed that for a fixed robot stride frequency, velocity and stride length increase with increasing saturation, confirming the locomotion characteristics of the Basilisk lizard. It is further observed that with increasing saturation level, robot cost of transport decreases. An identical series of robot experiments are performed with quadrupedal gait to determine effects of gait parameters on robot performance. Generally, energetics of bipedal running is observed to be higher than quadrupedal operation. Experimental results also reveal how gait parameters can be varied to achieve different desired velocities depending on the substrate saturation level. In addition to robot experiments on granular media, a series of animal experiments are conducted to determine and characterize strategies
exhibited by Basilisk lizards when transitioning from granular to aquatic media.
exhibited by Basilisk lizards when transitioning from granular to aquatic media.
ContributorsJayanetti, Vidu (Author) / Marvi, Hamid (Thesis advisor) / Emady, Heather (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2018