Matching Items (13)
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- All Subjects: robotics
- Genre: Masters Thesis
- Creators: Sugar, Thomas
- Creators: Turaga, Pavan
Description
One of the main challenges in planetary robotics is to traverse the shortest path through a set of waypoints. The shortest distance between any two waypoints is a direct linear traversal. Often times, there are physical restrictions that prevent a rover form traversing straight to a waypoint. Thus, knowledge of the terrain is needed prior to traversal. The Digital Terrain Model (DTM) provides information about the terrain along with waypoints for the rover to traverse. However, traversing a set of waypoints linearly is burdensome, as the rovers would constantly need to modify their orientation as they successively approach waypoints. Although there are various solutions to this problem, this research paper proposes the smooth traversability of the rover using splines as a quick and easy implementation to traverse a set of waypoints. In addition, a rover was used to compare the smoothness of the linear traversal along with the spline interpolations. The data collected illustrated that spline traversals had a less rate of change in the velocity over time, indicating that the rover performed smoother than with linear paths.
ContributorsKamasamudram, Anurag (Author) / Saripalli, Srikanth (Thesis advisor) / Fainekos, Georgios (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
With robots being used extensively in various areas, a certain degree of robot autonomy has always been found desirable. In applications like planetary exploration, autonomous path planning and navigation are considered essential. But every now and then, a need to modify the robot's operation arises, a need for a human to provide it some supervisory parameters that modify the degree of autonomy or allocate extra tasks to the robot. In this regard, this thesis presents an approach to include a provision to accept and incorporate such human inputs and modify the navigation functions of the robot accordingly. Concepts such as applying kinematical constraints while planning paths, traversing of unknown areas with an intent of maximizing field of view, performing complex tasks on command etc. have been examined and implemented. The approaches have been tested in Robot Operating System (ROS), using robots such as the iRobot Create, Personal Robotics (PR2) etc. Simulations and experimental demonstrations have proved that this approach is feasible for solving some of the existing problems and that it certainly can pave way to further research for enhancing functionality.
ContributorsVemprala, Sai Hemachandra (Author) / Saripalli, Srikanth (Thesis advisor) / Fainekos, Georgios (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Fisheye cameras are special cameras that have a much larger field of view compared to
conventional cameras. The large field of view comes at a price of non-linear distortions
introduced near the boundaries of the images captured by such cameras. Despite this
drawback, they are being used increasingly in many applications of computer vision,
robotics, reconnaissance, astrophotography, surveillance and automotive applications.
The images captured from such cameras can be corrected for their distortion if the
cameras are calibrated and the distortion function is determined. Calibration also allows
fisheye cameras to be used in tasks involving metric scene measurement, metric
scene reconstruction and other simultaneous localization and mapping (SLAM) algorithms.
This thesis presents a calibration toolbox (FisheyeCDC Toolbox) that implements a collection of some of the most widely used techniques for calibration of fisheye cameras under one package. This enables an inexperienced user to calibrate his/her own camera without the need for a theoretical understanding about computer vision and camera calibration. This thesis also explores some of the applications of calibration such as distortion correction and 3D reconstruction.
conventional cameras. The large field of view comes at a price of non-linear distortions
introduced near the boundaries of the images captured by such cameras. Despite this
drawback, they are being used increasingly in many applications of computer vision,
robotics, reconnaissance, astrophotography, surveillance and automotive applications.
The images captured from such cameras can be corrected for their distortion if the
cameras are calibrated and the distortion function is determined. Calibration also allows
fisheye cameras to be used in tasks involving metric scene measurement, metric
scene reconstruction and other simultaneous localization and mapping (SLAM) algorithms.
This thesis presents a calibration toolbox (FisheyeCDC Toolbox) that implements a collection of some of the most widely used techniques for calibration of fisheye cameras under one package. This enables an inexperienced user to calibrate his/her own camera without the need for a theoretical understanding about computer vision and camera calibration. This thesis also explores some of the applications of calibration such as distortion correction and 3D reconstruction.
ContributorsKashyap Takmul Purushothama Raju, Vinay (Author) / Karam, Lina (Thesis advisor) / Turaga, Pavan (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Human running requires extensive training and conditioning for an individual to maintain high speeds (greater than 10mph) for an extended duration of time. Studies have shown that running at peak speeds generates a high metabolic cost due to the use of large muscle groups in the legs associated with the human gait cycle. Applying supplemental external and internal forces to the human body during the gait cycle has been shown to decrease the metabolic cost for walking, allowing individuals to carry additional weight and walk further distances. Significant research has been conducted to reduce the metabolic cost of walking, however, there are few if any documented studies that focus specifically on reducing the metabolic cost associated with high speed running. Three mechanical systems were designed to work in concert with the human user to decrease metabolic cost and increase the range and speeds at which a human can run.
The methods of design require a focus on mathematical modeling, simulations, and metabolic cost. Mathematical modeling and simulations are used to aid in the design process of robotic systems and metabolic testing is regarded as the final analysis process to determine the true effectiveness of robotic prototypes. Metabolic data, (VO2) is the volumetric consumption of oxygen, per minute, per unit mass (ml/min/kg). Metabolic testing consists of analyzing the oxygen consumption of a test subject while performing a task naturally and then comparing that data with analyzed oxygen consumption of the same task while using an assistive device.
Three devices were designed and tested to augment high speed running. The first device, AirLegs V1, is a mostly aluminum exoskeleton with two pneumatic linear actuators connecting from the lower back directly to the user's thighs, allowing the device to induce a torque on the leg by pushing and pulling on the user's thigh during running. The device also makes use of two smaller pneumatic linear actuators which drive cables connecting to small lever arms at the back of the heel, inducing a torque at the ankles. Device two, AirLegs V2, is also pneumatically powered but is considered to be a soft suit version of the first device. It uses cables to interface the forces created by actuators located vertically on the user's back. These cables then connect to the back of the user's knees resulting in greater flexibility and range of motion of the legs. Device three, a Jet Pack, produces an external force against the user's torso to propel a user forward and upward making it easier to run. Third party testing, pilot demonstrations and timed trials have demonstrated that all three of the devices effectively reduce the metabolic cost of running below that of natural running with no device.
The methods of design require a focus on mathematical modeling, simulations, and metabolic cost. Mathematical modeling and simulations are used to aid in the design process of robotic systems and metabolic testing is regarded as the final analysis process to determine the true effectiveness of robotic prototypes. Metabolic data, (VO2) is the volumetric consumption of oxygen, per minute, per unit mass (ml/min/kg). Metabolic testing consists of analyzing the oxygen consumption of a test subject while performing a task naturally and then comparing that data with analyzed oxygen consumption of the same task while using an assistive device.
Three devices were designed and tested to augment high speed running. The first device, AirLegs V1, is a mostly aluminum exoskeleton with two pneumatic linear actuators connecting from the lower back directly to the user's thighs, allowing the device to induce a torque on the leg by pushing and pulling on the user's thigh during running. The device also makes use of two smaller pneumatic linear actuators which drive cables connecting to small lever arms at the back of the heel, inducing a torque at the ankles. Device two, AirLegs V2, is also pneumatically powered but is considered to be a soft suit version of the first device. It uses cables to interface the forces created by actuators located vertically on the user's back. These cables then connect to the back of the user's knees resulting in greater flexibility and range of motion of the legs. Device three, a Jet Pack, produces an external force against the user's torso to propel a user forward and upward making it easier to run. Third party testing, pilot demonstrations and timed trials have demonstrated that all three of the devices effectively reduce the metabolic cost of running below that of natural running with no device.
ContributorsKerestes, Jason (Author) / Sugar, Thomas (Thesis advisor) / Redkar, Sangram (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2014
Description
Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find better solutions. In this thesis, a novel method is proposed which uses image registration techniques to provide better image classification. This method reduces the error rate of classification by performing image registration of the images with the previously obtained images before performing classification. The motivation behind this is the fact that images that are obtained in the same region which need to be classified will not differ significantly in characteristics. Hence, registration will provide an image that matches closer to the previously obtained image, thus providing better classification. To illustrate that the proposed method works, naïve Bayes and iterative closest point (ICP) algorithms are used for the image classification and registration stages respectively. This implementation was tested extensively in simulation using synthetic images and using a real life data set called the Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) dataset. The results show that the ICP algorithm does help in better classification with Naïve Bayes by reducing the error rate by an average of about 10% in the synthetic data and by about 7% on the actual datasets used.
ContributorsMuralidhar, Ashwini (Author) / Saripalli, Srikanth (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Simultaneous localization and mapping (SLAM) has traditionally relied on low-level geometric or optical features. However, these features-based SLAM methods often struggle with feature-less or repetitive scenes. Additionally, low-level features may not provide sufficient information for robot navigation and manipulation, leaving robots without a complete understanding of the 3D spatial world. Advanced information is necessary to address these limitations. Fortunately, recent developments in learning-based 3D reconstruction allow robots to not only detect semantic meanings, but also recognize the 3D structure of objects from a few images. By combining this 3D structural information, SLAM can be improved from a low-level approach to a structure-aware approach. This work propose a novel approach for multi-view 3D reconstruction using recurrent transformer. This approach allows robots to accumulate information from multiple views and encode them into a compact latent space. The resulting latent representations are then decoded to produce 3D structural landmarks, which can be used to improve robot localization and mapping.
ContributorsHuang, Chi-Yao (Author) / Yang, Yezhou (Thesis advisor) / Turaga, Pavan (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2023
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
Description
This thesis presents the design and testing of a soft robotic device for water utility pipeline inspection. The preliminary findings of this new approach to conventional methods of pipe inspection demonstrate that a soft inflatable robot can successfully traverse the interior space of a range of diameter pipes using pneumatic and without the need to adjust rigid, mechanical components. The robot utilizes inflatable soft actuators with an adjustable radius which, when pressurized, can provide a radial force, effectively anchoring the device in place. Additional soft inflatable actuators translate forces along the center axis of the device which creates forward locomotion when used in conjunction with the radial actuation. Furthermore, a bio-inspired control algorithm for locomotion allows the robot to maneuver through a pipe by mimicking the peristaltic gait of an inchworm. This thesis provides an examination and evaluation of the structure and behavior of the inflatable actuators through computational modeling of the material and design, as well as the experimental data of the forces and displacements generated by the actuators. The theoretical results are contrasted with/against experimental data utilizing a physical prototype of the soft robot. The design is anticipated to enable compliant robots to conform to the space offered to them and overcome occlusions from accumulated solids found in pipes. The intent of the device is to be used for inspecting existing pipelines owned and operated by Salt River Project, a Phoenix-area water and electricity utility provider.
ContributorsAdams, Wade Silas (Author) / Aukes, Daniel (Thesis advisor) / Sugar, Thomas (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2019
Description
As the world population continues to age, the demand for treatment and rehabilitation of long-term age-related ailments will rise. Healthcare technology must keep up with this demand, and existing solutions must become more readily available to the populace. Conditions such as impairment due to stroke currently take months or years of physical therapy to overcome, but rehabilitative exoskeletons can be used to greatly extend a physical therapist’s capabilities.
In this thesis, a rehabilitative knee exoskeleton was designed which is significantly lighter, more portable and less costly to manufacture than existing designs. It accomplishes this performance by making use of high-powered and weight-optimized brushless DC (BLDC) electric motors designed for drones, open-source hardware and software solutions for robotic motion control, and rapid prototyping technologies such as 3D printing and laser cutting.
The exoskeleton is made from a series of laser cut aluminum plates spaced apart with off-the-shelf standoffs. A drone motor with a torque of 1.32 Nm powers an 18.5:1 reduction two-stage belt drive, giving a maximum torque of 24.4 Nm at the output. The bearings for the belt drive are installed into 3D printed bearing mounts, which act as a snug intermediary between the bearing and the aluminum plate. The system is powered off a 24 volt, 1,500 MAh lithium battery, which can provide power for around an hour of walking activity.
The exoskeleton is controlled with an ODrive motor controller connected to a Raspberry Pi. Hip angle data is provided by an IMU, and the knee angle is provided by an encoder on the output shaft. A compact Rotary Series Elastic Actuator (cRSEA) device is mounted on the output shaft as well, to accurately measure the output torque going to the wearer. A Proportional-Derivative (PD) controller with feedforward relates the input current with the output torque. The device was tested on a treadmill and found to have an average backdrive torque of 0.39 Nm, significantly lower than the current state of the art. A gravity compensation controller and impedance controller were implemented to assist during swing and stance phases respectively. The results were compared to the muscular exertion of the knee measured via Electromyography (EMG).
In this thesis, a rehabilitative knee exoskeleton was designed which is significantly lighter, more portable and less costly to manufacture than existing designs. It accomplishes this performance by making use of high-powered and weight-optimized brushless DC (BLDC) electric motors designed for drones, open-source hardware and software solutions for robotic motion control, and rapid prototyping technologies such as 3D printing and laser cutting.
The exoskeleton is made from a series of laser cut aluminum plates spaced apart with off-the-shelf standoffs. A drone motor with a torque of 1.32 Nm powers an 18.5:1 reduction two-stage belt drive, giving a maximum torque of 24.4 Nm at the output. The bearings for the belt drive are installed into 3D printed bearing mounts, which act as a snug intermediary between the bearing and the aluminum plate. The system is powered off a 24 volt, 1,500 MAh lithium battery, which can provide power for around an hour of walking activity.
The exoskeleton is controlled with an ODrive motor controller connected to a Raspberry Pi. Hip angle data is provided by an IMU, and the knee angle is provided by an encoder on the output shaft. A compact Rotary Series Elastic Actuator (cRSEA) device is mounted on the output shaft as well, to accurately measure the output torque going to the wearer. A Proportional-Derivative (PD) controller with feedforward relates the input current with the output torque. The device was tested on a treadmill and found to have an average backdrive torque of 0.39 Nm, significantly lower than the current state of the art. A gravity compensation controller and impedance controller were implemented to assist during swing and stance phases respectively. The results were compared to the muscular exertion of the knee measured via Electromyography (EMG).
ContributorsParmentier, Robin W (Author) / Zhang, Wenlong (Thesis advisor) / Sugar, Thomas (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2020
Description
Bicycles and motorcycles offer maneuverability, energy efficiency and acceleration that four wheeled vehicles cannot offer given similar budget for. Two wheeled vehicles have drastically different dynamics from four wheeled vehicles due to their instability and gyroscopic effect from their wheels.
This thesis focuses on self-stabilization of a motorcycle using an active control momentum gyroscope (CMG) and validation of this multi-degree-of-freedom system’s mathematical model. Physical platform was created to mimic the simulation as accurately as possible and all components used were justified. This process involves derivation of a 3 Degree-of-Freedom (DOF) system’s forward kinematics and its Jacobian matrix, simulation analysis of different controller algorithms, setting the system and subsystem specifications, and real system experimentation and data analysis.
A Jacobian matrix was used to calculate accurately decomposed resultant angular velocities which are used to create the dynamics model of the system torque using the Euler-Lagrange method. This produces a nonlinear second order differential equation that is modeled using MATLAB/Simulink. PID, and cascaded feedback loop are tested in this Simulink model. Cascaded feedback loop shows most promises in the simulation analysis. Therefore, system specifications are calculated according to the data produced by this controller method. The model validation is executed using the Vicon motion capture system which captured the roll angle of the motorcycle. This work contributes to creating a set of procedures for creating a validated dynamic model for a CMG stabilized motorcycle which can be used to create variants of other self-stabilizing motorcycle system.
This thesis focuses on self-stabilization of a motorcycle using an active control momentum gyroscope (CMG) and validation of this multi-degree-of-freedom system’s mathematical model. Physical platform was created to mimic the simulation as accurately as possible and all components used were justified. This process involves derivation of a 3 Degree-of-Freedom (DOF) system’s forward kinematics and its Jacobian matrix, simulation analysis of different controller algorithms, setting the system and subsystem specifications, and real system experimentation and data analysis.
A Jacobian matrix was used to calculate accurately decomposed resultant angular velocities which are used to create the dynamics model of the system torque using the Euler-Lagrange method. This produces a nonlinear second order differential equation that is modeled using MATLAB/Simulink. PID, and cascaded feedback loop are tested in this Simulink model. Cascaded feedback loop shows most promises in the simulation analysis. Therefore, system specifications are calculated according to the data produced by this controller method. The model validation is executed using the Vicon motion capture system which captured the roll angle of the motorcycle. This work contributes to creating a set of procedures for creating a validated dynamic model for a CMG stabilized motorcycle which can be used to create variants of other self-stabilizing motorcycle system.
ContributorsMoon, Hansol (Author) / Zhang, Wenlong (Thesis advisor) / Frank, Daniel (Committee member) / Delp, Deana (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2020