Matching Items (14)
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- All Subjects: robotics
- Genre: Masters Thesis
- Creators: Aukes, Daniel
- 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
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
What if there is a way to integrate prosthetics seamlessly with the human body and robots could help improve the lives of children with disabilities? With physical human-robot interaction being seen in multiple aspects of life, including industry, medical, and social, how these robots are interacting with human becomes even more important. Therefore, how smoothly the robot can interact with a person will determine how safe and efficient this relationship will be. This thesis investigates adaptive control method that allows a robot to adapt to the human's actions based on the interaction force. Allowing the relationship to become more effortless and less strained when the robot has a different goal than the human, as seen in Game Theory, using multiple techniques that adapts the system. Few applications this could be used for include robots in physical therapy, manufacturing robots that can adapt to a changing environment, and robots teaching people something new like dancing or learning how to walk after surgery.
The experience gained is the understanding of how a cost function of a system works, including the tracking error, speed of the system, the robot’s effort, and the human’s effort. Also, this two-agent system, results into a two-agent adaptive impedance model with an input for each agent of the system. This leads to a nontraditional linear quadratic regulator (LQR), that must be separated and then added together. Thus, creating a traditional LQR. This new experience can be used in the future to help build better safety protocols on manufacturing robots. In the future the knowledge learned from this research could be used to develop technologies for a robot to allow to adapt to help counteract human error.
The experience gained is the understanding of how a cost function of a system works, including the tracking error, speed of the system, the robot’s effort, and the human’s effort. Also, this two-agent system, results into a two-agent adaptive impedance model with an input for each agent of the system. This leads to a nontraditional linear quadratic regulator (LQR), that must be separated and then added together. Thus, creating a traditional LQR. This new experience can be used in the future to help build better safety protocols on manufacturing robots. In the future the knowledge learned from this research could be used to develop technologies for a robot to allow to adapt to help counteract human error.
ContributorsBell, Rebecca C (Author) / Zhang, Wenlong (Thesis advisor) / Chiou, Erin (Committee member) / Aukes, Daniel (Committee member) / Arizona State University (Publisher)
Created2019
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
Existing robotic excavation research has been primarily focused on lunar mining missions or simple traffic control in confined tunnels, however little work attempts to bring collective excavation into the realm of human infrastructure. This thesis explores a decentralized approach to excavation processes, where traffic laws are borrowed from swarms of fire ants (Solenopsis invicta) or termites (Coptotermes formosanus) to create decision rules for a swarm of robots working together and organizing effectively to create a desired final excavated pattern.
First, a literature review of the behavioral rules of different types of insect colonies and the resulting structural patterns over the course of excavation was conducted. After identifying pertinent excavation laws, three different finite state machines were generated that relate to construction, search and rescue operations, and extraterrestrial exploration. After analyzing these finite state machines, it became apparent that they all shared a common controller. Then, agent-based NetLogo software was used to simulate a swarm of agents that run this controller, and a model for excavating behaviors and patterns was fit to the simulation data. This model predicts the tunnel shapes formed in the simulation as a function of the swarm size and a time delay, called the critical waiting period, in one of the state transitions. Thus, by controlling the individual agents' behavior, it was possible to control the structural outcomes of collective excavation in simulation.
To create an experimental testbed that could be used to physically implement the controller, a small foldable robotic platform was developed, and it's capabilities were tested in granular media. In order to characterize the granular media, force experiments were conducted and parameters were measured for resistive forces during an excavation cycle. The final experiment verified the robot's ability to engage in excavation and deposition, and to determine whether or not to begin the critical waiting period. This testbed can be expanded with multiple robots to conduct small-scale experiments on collective excavation, such as further exploring the effects of the critical waiting period on the resulting excavation pattern. In addition, investigating other factors like tuning digging efficiency or deposition proximity could help to transition the proposed bio-inspired swarm excavation controllers to implementation in real-world applications.
First, a literature review of the behavioral rules of different types of insect colonies and the resulting structural patterns over the course of excavation was conducted. After identifying pertinent excavation laws, three different finite state machines were generated that relate to construction, search and rescue operations, and extraterrestrial exploration. After analyzing these finite state machines, it became apparent that they all shared a common controller. Then, agent-based NetLogo software was used to simulate a swarm of agents that run this controller, and a model for excavating behaviors and patterns was fit to the simulation data. This model predicts the tunnel shapes formed in the simulation as a function of the swarm size and a time delay, called the critical waiting period, in one of the state transitions. Thus, by controlling the individual agents' behavior, it was possible to control the structural outcomes of collective excavation in simulation.
To create an experimental testbed that could be used to physically implement the controller, a small foldable robotic platform was developed, and it's capabilities were tested in granular media. In order to characterize the granular media, force experiments were conducted and parameters were measured for resistive forces during an excavation cycle. The final experiment verified the robot's ability to engage in excavation and deposition, and to determine whether or not to begin the critical waiting period. This testbed can be expanded with multiple robots to conduct small-scale experiments on collective excavation, such as further exploring the effects of the critical waiting period on the resulting excavation pattern. In addition, investigating other factors like tuning digging efficiency or deposition proximity could help to transition the proposed bio-inspired swarm excavation controllers to implementation in real-world applications.
ContributorsHaggerty, Zz Mae (Author) / Berman, Spring M (Thesis advisor) / Aukes, Daniel (Committee member) / Marvi, Hamid (Committee member) / Arizona State University (Publisher)
Created2018
Description
Foldable robots have gained popularity in recent years due to their versatility and portability. However, the use of composite hinges in these systems has posed challenges in terms of manufacturing complexity and cost. Historically, single material robots were very limited due to the fact that both the link and the hinge are made with the same material and striking a balance with stiffness of the link and flexibility of the hinge has been very difficult. Hinges would undergo fatigue within hundreds of cycles and show non-linear wear and physical properties. This research proposes an innovative approach to simplify foldable robotics by replacing composite hinges with single material flexure hinges. The proposed hinges are manufactured using a CO2 laser cutter and are designed to enhance performance and reduce costs over previous single-layer-hinges. A mathematical model has been developed to predict the behavior of the hinges and tune them to the desired requirements. Experimental results show that the proposed hinges offer improved flexibility and durability compared to single-layer hinges, while reducing the manufacturing cost and complexity associated with multi-layer hinges. This research contributes to the advancement of foldable robotics by offering a simplified and cost-effective solution that can foster innovation in various applications.
ContributorsKanchan, Viraj (Author) / Aukes, Daniel (Thesis advisor) / Redkan, Sangram (Committee member) / Sugar, Thmas (Committee member) / Arizona State University (Publisher)
Created2023