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- All Subjects: robotics
- Genre: Masters Thesis
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
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
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
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
Linear Temporal Logic is gaining increasing popularity as a high level specification language for robot motion planning due to its expressive power and scalability of LTL control synthesis algorithms. This formalism, however, requires expert knowledge and makes it inaccessible to non-expert users. This thesis introduces a graphical specification environment to create high level motion plans to control robots in the field by converting a visual representation of the motion/task plan into a Linear Temporal Logic (LTL) specification. The visual interface is built on the Android tablet platform and provides functionality to create task plans through a set of well defined gestures and on screen controls. It uses the notion of waypoints to quickly and efficiently describe the motion plan and enables a variety of complex Linear Temporal Logic specifications to be described succinctly and intuitively by the user without the need for the knowledge and understanding of LTL specification. Thus, it opens avenues for its use by personnel in military, warehouse management, and search and rescue missions. This thesis describes the construction of LTL for various scenarios used for robot navigation using the visual interface developed and leverages the use of existing LTL based motion planners to carry out the task plan by a robot.
ContributorsSrinivas, Shashank (Author) / Fainekos, Georgios (Thesis advisor) / Baral, Chitta (Committee member) / Burleson, Winslow (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
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
As the complexity of robotic systems and applications grows rapidly, development of high-performance, easy to use, and fully integrated development environments for those systems is inevitable. Model-Based Design (MBD) of dynamic systems using engineering software such as Simulink® from MathWorks®, SciCos from Metalau team and SystemModeler® from Wolfram® is quite popular nowadays. They provide tools for modeling, simulation, verification and in some cases automatic code generation for desktop applications, embedded systems and robots. For real-world implementation of models on the actual hardware, those models should be converted into compilable machine code either manually or automatically. Due to the complexity of robotic systems, manual code translation from model to code is not a feasible optimal solution so we need to move towards automated code generation for such systems. MathWorks® offers code generation facilities called Coder® products for this purpose. However in order to fully exploit the power of model-based design and code generation tools for robotic applications, we need to enhance those software systems by adding and modifying toolboxes, files and other artifacts as well as developing guidelines and procedures. In this thesis, an effort has been made to propose a guideline as well as a Simulink® library, StateFlow® interface API and a C/C++ interface API to complete this toolchain for NAO humanoid robots. Thus the model of the hierarchical control architecture can be easily and properly converted to code and built for implementation.
ContributorsRaji Kermani, Ramtin (Author) / Fainekos, Georgios (Thesis advisor) / Lee, Yann-Hang (Committee member) / Sarjoughian, Hessam S. (Committee member) / Arizona State University (Publisher)
Created2013
Description
The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog of the transmission LMP (DLMP) as an enabler of the advanced applications of the enhanced distribution system. The DLMP is envisioned as a control signal that can incentivize distribution system resources to behave optimally in a manner that benefits economic efficiency and system reliability and that can optimally couple the transmission and the distribution systems. The DLMP is calculated from a two-stage optimization problem; a transmission system OPF and a distribution system OPF. An iterative framework that ensures accurate representation of the distribution system's price sensitive resources for the transmission system problem and vice versa is developed and its convergence problem is discussed. As part of the DLMP calculation framework, a DCOPF formulation that endogenously captures the effect of real power losses is discussed. The formulation uses piecewise linear functions to approximate losses. This thesis explores, with theoretical proofs, the breakdown of the loss approximation technique when non-positive DLMPs/LMPs occur and discusses a mixed integer linear programming formulation that corrects the breakdown. The DLMP is numerically illustrated in traditional and enhanced distribution systems and its superiority to contemporary pricing mechanisms is demonstrated using price responsive loads. Results show that the impact of the inaccuracy of contemporary pricing schemes becomes significant as flexible resources increase. At high elasticity, aggregate load consumption deviated from the optimal consumption by up to about 45 percent when using a flat or time-of-use rate. Individual load consumption deviated by up to 25 percent when using a real-time price. The superiority of the DLMP is more pronounced when important distribution network conditions are not reflected by contemporary prices. The individual load consumption incentivized by the real-time price deviated by up to 90 percent from the optimal consumption in a congested distribution network. While the DLMP internalizes congestion management, the consumption incentivized by the real-time price caused overloads.
ContributorsAkinbode, Oluwaseyi Wemimo (Author) / Hedman, Kory W (Thesis advisor) / Heydt, Gerald T (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013
Description
Tolerances on line profiles are used to control cross-sectional shapes of parts, such as turbine blades. A full life cycle for many mechanical devices depends (i) on a wise assignment of tolerances during design and (ii) on careful quality control of the manufacturing process to ensure adherence to the specified tolerances. This thesis describes a new method for quality control of a manufacturing process by improving the method used to convert measured points on a part to a geometric entity that can be compared directly with tolerance specifications. The focus of this paper is the development of a new computational method for obtaining the least-squares fit of a set of points that have been measured with a coordinate measurement machine along a line-profile. The pseudo-inverse of a rectangular matrix is used to convert the measured points to the least-squares fit of the profile. Numerical examples are included for convex and concave line-profiles, that are formed from line- and circular arc-segments.
ContributorsSavaliya, Samir (Author) / Davidson, Joseph K. (Thesis advisor) / Shah, Jami J. (Committee member) / Santos, Veronica J (Committee member) / Arizona State University (Publisher)
Created2013