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Lewinger, William AnthonyNeurobiologically-based Control System for an Adaptively Walking Hexapod
Doctor of Philosophy, Case Western Reserve University, 2011, EECS - System and Control Engineering

Biological systems such as insects have often been used as a source of inspiration when developing legged robots. Insects are capable of nimbly navigating uneven terrain. This ability, combined with their observed behavioral complexity has made them a beacon for engineers, who have used behavioral data and hypothesized control systems to develop remarkably agile robots. Beyond pure inspiration, it is now becoming possible to directly implement models of relatively recent discoveries in insect nervous systems in hexapod robot controllers. Specifically, walking control based on a model of a network discovered in the stick insect’s thoracic ganglia, and not just observed insect behavior, has now been implemented in a complete hexapod that is able to walk, perform a goal-seeking behavior, and obstacle surmounting behaviors such as single limb searching and elevator reflexes. Descending modulation of leg controllers is also incorporated via a “head module” that modifies leg controller parameters to accomplish turning in a role similar to the insect’s higher centers. While many of these features have been previously demonstrated in simulation and with robotic subsystems, such as single- and two-legged test platforms, this is the first time that these neurobiological methods of control have been implemented in a complete, autonomous walking hexapod.

Many of these abilities have also been incorporated in previous hexapods by using more traditional engineering methods and methods based on external observations of insects. However, the methods described and used in this research, which are based on the actual neurobiological circuits found in the insect, are far simpler and therefore have much lower computational requirements. The reduced computation requirements lend themselves to small robots with limited on-board space available for the high-end processors needed for previous control methods.

This dissertation discusses the implementation of the biologically-grounded insect leg control method, descending modulation of that method, and the generation of stable, speed-dependent gaits. It then describes and quantifies the performance of the robot while navigating irregular terrain and performing phototaxis. Implementation is performed on the Biologically-Inspired Legged Locomotion - Ant - autonomous (BILL-Ant-a) hexapod robot.

Committee:

Roger Quinn, PhD (Advisor); Roy Ritzmann, PhD (Committee Member); Michael Branicky, PhD (Committee Member); Wyatt Newman, PhD (Committee Member)

Subjects:

Biology; Computer Science; Electrical Engineering; Mechanical Engineering; Neurobiology; Robotics; Systems Design

Keywords:

biologically-inspired; neurobiology; robotics; legged robotics; hexapod; leg control; mobile robots

Andersen, Kayla BA Nitinol Actuated Worm-Inspired Robot Capable of Forward Motion, Turning, and Climbing Obstacles
Master of Sciences, Case Western Reserve University, 2017, EMC - Mechanical Engineering
This thesis introduces a new worm-inspired robot made of a pre-fabricated mesh and nitinol shape memory alloy springs. The unique arrangement of actuators enables the robot to move forward, turn left and right, lift its front segments into the air, and surmount an obstacle 14% of the robot’s diameter. Multiple iterations resulted in a prototype capable of moving forward at a speed of 0.88cm/min. While testing the robot over multiple days, a significant deterioration in performance was observed. The nitinol actuators were identified as the likely cause of the degradation, after considering other potential causes. To validate or disprove this hypothesis, preliminary experiments on the effects of cyclic thermomechanical loading of the nitinol springs were conducted. The preliminary results suggest inadequate cooling time between cycles leads to a shifting of the set-point of the nitinol spring, even if the temperature is below the transition temperature of the nitinol.

Committee:

Roger Quinn (Advisor); Hillel Chiel (Committee Member); Richard Bachmann (Committee Member)

Subjects:

Engineering

Keywords:

soft robotics, robotics, worm-inspired, earthworm, nitinol

Hecht, Steven ADriving by Speaking: Natural Language Control of Robotic Wheelchairs
Master of Sciences (Engineering), Case Western Reserve University, 2013, EECS - Electrical Engineering
While many people use electric wheelchairs to enhance their mobility, there are groups who cannot due to age, injury, or cognitive impairment. A voice-operated smart wheelchair would greatly enhance the self-mobility of these users. This thesis presents a method to parse natural language commands into useful robotic instructions as well as control methods to navigate in a priori known and novel environments. An agglomerative algorithm was developed that uses stemmatic processing to extract meaning from natural language commands. A method for creating a navigable graph from a simplified blueprint is introduced. A MATLAB simulation was created to simulate navigation in a novel building using sensory data obtained from a virtual LIDAR. The natural language navigation control algorithms have been tested for destination-based and landmark-based navigation and perform well on simple commands.

Committee:

Gregory Lee, PhD (Advisor); Francis Merat, PhD (Committee Member); M. Cenk Cavusoglu, PhD (Committee Member)

Subjects:

Robotics

Keywords:

Mobile Robotics; Cognitive Robotics; Natural Language Processing; Navigation; Simulation

Tietz, Brian R.MODELS OF COCKROACH SHELTER SEEKING IMPLEMENTED ON A ROBOTIC TEST PLATFORM
Master of Sciences (Engineering), Case Western Reserve University, 2012, EMC - Mechanical Engineering
Animal behavior is often a model for robotic control, with benefits for both robotics and biology. This research covers a new animal behavior for this category: cockroach shelter seeking. Cockroach behavior was tracked in a 91 cm by 91 cm arena, and significant trends were identified that form a stochastic navigation algorithm called RAMBLER. Components of RAMBLER were then implemented on a mobile robot, and compared with a deterministic model of the same cockroach behaviors. In the process of programming the robotic model, an interesting behavior was discovered when the cockroach loses contact with a barrier in the arena, posing new questions about animal behavior.

Committee:

Roger Quinn, PhD (Committee Chair); Roy Ritzmann, PhD (Committee Member); Michael Branicky, PhD (Committee Member)

Subjects:

Mechanical Engineering; Neurobiology

Keywords:

Cockroach; Robotics; Biologically-Inspired Robotics; Neuroethology; Neurobiology; Mechanical Engineering; Behavioral Biology;

Boxerbaum, Alexander SteeleContinuous Wave Peristaltic Motion in a Robot
Doctor of Philosophy, Case Western Reserve University, 2012, EMC - Mechanical Engineering
This dissertation is a study of peristalsis, the method of locomotion earthworms use, and how to best achieve this in a robotic platform. A technique is presented that uses a braided mesh exterior to produce smooth waves of motion along the body of a worm-like robot. This braided mesh can be powered by a one degree-of-freedom cam mechanism, which is demonstrated, or by several independent motors. A new analytical model of peristalsis is presented and predicted robot velocity is compared to a 2-D simulation and a working prototype. It has been often assumed that this motion requires strong anisotropic ground friction. However, our analysis shows that with uniform, constant velocity waves, the forces that cause accelerations within the body sum to zero. Instead, transition timing between aerial and ground phases and the ability to generate strain play a critical role in the final robot speed. Lastly, we present a soft-body controller that uses simulated neuronal populations. This controller is designed for the next generation of soft, hyper-redundant systems and can intrinsically generate waves of a desired behavior while smoothly incorporating large amounts of simulated sensory input.

Committee:

Roger Quinn, D (Advisor); HIllel Chiel (Advisor); Malcolm Cooke (Committee Member); Joseph Mansour (Committee Member)

Subjects:

Biomechanics; Mechanical Engineering; Robotics

Keywords:

soft robotics; biologically inspired robotics; peristalsis; biorobots; hyper-redundant; soft body control; neuronal modeling

Hester, Matthew S.Stable Control of Jumping in a Planar Biped Robot
Master of Science, The Ohio State University, 2009, Mechanical Engineering

The ability to perform high-speed dynamic maneuvers is an important aspect of locomotion for bipedal animals such as humans. Running, jumping, and rapidly changing direction are fundamental dynamic maneuvers that contribute to the adaptability and performance required for bipeds to move through unstructured environments. A number of bipedal robots have been produced to investigate dynamic maneuvers. However, the level of performance demonstrated by biological systems has yet to be fully realized in a biped robot. One limiting factor in achieving comparable performance to animals is the lack of available control strategies that can successfully coordinate dynamic maneuvers. This thesis develops a control strategy for producing vertical jumping in a planar biped robot as a preliminary investigation into dynamic maneuvers. The control strategy was developed using a modular approach to allow adaptation to further dynamic maneuvers and robotic systems.

The control strategy was broken into two functional levels to separately solve the problems of planning and performing the jump maneuver. The jump is performed using a low-level controller, consisting of a state machine for determining the current phase of the jump and motor primitives for executing the joint motions required by the current phase. The motor primitives, described by open- and closed-loop control laws, were defined with numeric control parameters for modifying their performance. The high-level controller performs the task of planning the motion required to achieve the desired jump height. Fuzzy control, an intelligent control approach, was selected for the high-level controller. The fuzzy controller uses heuristic information about the biped system to select appropriate control parameters. This heuristic knowledge was implemented in a training algorithm. The training algorithm uses iterative jumps with error-based feedback to determine the control parameters to be implemented by the fuzzy controller.

The control strategy was developed and validated using a numerical simulation of the experimental biped KURMET. The simulation models the dynamics of the biped system and has demonstrated the ability of the control strategy to produce stable successive jumps with an approximate height of 0.575 m. The control strategy was also implemented on the experimental biped for a simplified case, resulting in stable successive jumps with a range of heights from 0.55 to 0.60 m.

Committee:

James Schmiedeler (Advisor); David Orin (Committee Member); Chia-Hsiang Menq (Committee Member)

Subjects:

Electrical Engineering; Engineering; Mechanical Engineering

Keywords:

biped;robot;KURMET;legged;locomotion;jump;jumping;robotics;fuzzy control;intelligent control;control strategy;

Jennings, Alan LanceAutonomous Motion Learning for Near Optimal Control
Doctor of Philosophy (Ph.D.), University of Dayton, 2012, Electrical Engineering

Human intelligence has appealed to the robotics community for a long time; specifically, a person's ability to learn new tasks efficiently and eventually master the task. This ability is the result of decades of development as a person matures from an infant to an adult and a similar developmental period seems to be required if robots are to obtain the ability to learn and master new skills. Applying developmental stages to robotics is a field of study that has been growing in acceptance. The paradigm shift is from directly pursuing the desired task to progressively building competencies until the desired task is reached. This dissertation seeks to apply a developmental approach to autonomous optimization of robotic motions, and the methods presented extend to function shaping and parameter optimization.

Humans have a limited ability to concentrate on multiple tasks at once. For robots with many degrees of freedom, human operators need a high-level interface, rather than controlling the positions of each angle. Motion primitives are scalable control signals that have repeatable, high-level results. Examples include walking, jumping or throwing where the result can be scaled in terms of speed, height or distance. Traditionally, motion primitives require extensive, robot-specific analysis making development of large databases of primitives infeasible. This dissertation presents methods of autonomously creating and refining optimal inverse functions for use as motion primitives. By clustering contiguous local optima, a continuous inverse function can be created by interpolating results. The additional clusters serve as alternatives if the chosen cluster is poorly suited to the situation. For multimodal problems, a population based optimization can efficiently search a large space.

Staged learning offers a path to mimic the progression from novice to master, as seen in human learning. The dimension of the input wave parameterization, which is the number degrees of freedom for optimization, is incremented to allow for additional improvement. As the parameterization increases in order, the true optimal continuous-time control signal is approached. All previous experiences can be directly moved to the higher parameterization when expanding the parameterization, if a proper parameterization is selected. Incrementally increasing complexity and retaining experience efficiently optimizes to high dimensions when contrasted with undirected global optimizations, which would need to search the entire high dimension space. The method presented allows for unbounded resolution since the parameterization is not fixed at programming.

This dissertation presents several methods that make steps towards the goal of learning and mastering motion-related tasks without programmed, task-specific heuristics. Trajectory optimization based on a high-level system description has been demonstrated for a robotic arm performing a pick-place task. In addition, the inverse optimal function was applied to optimizing robotic tracking precision in a method suitable for online tracking. Staging of the learning is able determine an optimal motor spin-up waveform despite large variations in system parameters. Global optimization, using a population based search, and unbounded resolution increasing provide the foundation for autonomously developing scalable motions superior to what can be designed by hand.

Committee:

Raúl Ordóñez, Ph. D. (Advisor); Frederick G. Harmon, Ph. D., Lt Col (Committee Member); Eric Balster, Ph. D. (Committee Member); Andrew Murray, Ph. D. (Committee Member)

Subjects:

Applied Mathematics; Artificial Intelligence; Electrical Engineering; Robotics; Robots

Keywords:

Nonlinear Optimization; Optimal Control; Developmental Learning; Robotics; Inverse Functions; Locally Weighted Regression

Yanick, Anthony JosephDriving By Speaking: Capabilities and Requirements of a Vocal Joystick
Master of Sciences, Case Western Reserve University, 2012, EECS - Computer Engineering
This thesis presents an investigation of prospects for driving a mobile robot or wheelchair with vocal commands. It is shown that latencies can degrade driving performance, which limits vocal commands to brief utterances. To command degrees of intensity of commands, such as curvature of turns, without benefit of multi-word expressions, it may be possible to encode additional information in prosodic features. Experimental results are presented indicating that prosody can be used to improve performance of a vocal interface. Prosodic features of rhythm, pitch and volume are examined to interpret how subjects use prosody to enhance driving commands, leading to suggestions of how to design a computer interface that exploits prosody.

Committee:

Wyatt Newman, PhD (Advisor); Patrizia Bonaventura, PhD (Committee Member); Gregory Lee (Committee Member)

Subjects:

Computer Engineering

Keywords:

Prosody; Mobile Robotics; Robotic Control; Semiotics; Cognitive Science

hart, charlesA Low-cost Omni-directional Visual Bearing Only Localization System
Master of Sciences, Case Western Reserve University, 2014, EECS - Computer and Information Sciences
RAMBLER Robot is designed to enable research on biologically inspired behavioral robot control algorithms. RAMBLER Robot tests the feasibility of autonomously localizing without typical sensors like wheel odometers or GPS. The primary objective is to independently, accurately, and robustly recover the path of a moving robotic system with only the lowest-cost sensors available off-the-shelf. Methods new and old are reviewed and tested on the real RAMBLER Robot hardware. The hardware and software necessary to use omni-directional camera measurements to decrease uncertainty regarding the position and heading of a small robot system are presented in detail. The RAMBLER Robot is shown to successfully localize within a small arena using three passive indistinguishable landmarks.

Committee:

Roger Quinn (Committee Chair); Francis Merat (Committee Member); Gregory Lee (Committee Member)

Subjects:

Computer Science; Robotics

Keywords:

omnicam; camera; omnidirectional; panoramic; catadioptric; spherical reflector; triangulation; power center; localization; particle filter; computer vision; raspberry pi; zumo; robot; robotics; low-cost; inexpensive; python; matlab; opencv;

Sneath, Evan BArtificial neural network training for semi-autonomous robotic surgery applications
MS, University of Cincinnati, 2014, Engineering and Applied Science: Computer Engineering
As telesurgical robots become more frequently used in surgical operating rooms, emphasis is shifting from human-controlled robotics to semi- or full automaticity. Safe and efficient methods of training and execution during an automated surgical task are required for real-world success. The approach of path generation using artificial neural networks allows for an effective and scalable solution for the supervised learning and real-time performance of a surgical procedure. This study makes use of long short-term memory (LSTM) recurrent neural networks (RNNs) in conjunction with the Evolino learning algorithm for tooltip path optimization. The RNNgenerated path is trained from human-performed procedures in a simulated testing environment. Changes in movement of path markers are accounted for by adjusting the tooltip acceleration with respect to target markers along the path. Results include smooth generated paths successfully meeting test procedure requirements of accuracy and speed in environments with both static and dynamic marker configurations.

Committee:

Fred Beyette, Ph.D. (Committee Chair); Ali Minai, Ph.D. (Committee Member); Grant Schaffner, Ph.D. (Committee Member)

Subjects:

Computer Engineering

Keywords:

telesurgery;robotics;artificial neural networks;evolino

Messay-Kebede, TemesguenComputationally Efficient and Robust Kinematic Calibration Methodologies and their Application to Industrial Robots
Doctor of Philosophy (Ph.D.), University of Dayton, 2014, Electrical Engineering
Robot kinematic calibration is the process of enhancing the positioning accuracy of a given manipulator and must be performed after robot manufacture and assembly or during periodical maintenance. This dissertation presents new computationally efficient and robust kinematic calibration algorithms for industrial robots that make use of partial measurements. These include a calibration method that requires the supply of Cartesian coordinates of the calibration points (3DCAL) and another calibration technique that only requires the radial measurements from the calibration points to some reference (1DCAL). Neither method requires orientation measurements nor the explicit knowledge of the where-about of a reference frame. Contrary to most other similar works, both methods make use of a simplified version of the original Denavit-Hartenberg (DH) kinematic model. The simplified DH(-) model has not only proven to be robust and effective in calibrating industrial manipulators but it is also favored from a computational efficiency viewpoint since it consists of comparatively fewer error parameters. We present a conceptual approach to develop a set of guidelines that need to be considered in order to properly construct the DH(-) model such that it is parameterically continuous and non-redundant. We also propose an automated method to provide a characterization of the parameters that can be insightful in identifying redundant/irrelevant parameters and deducing the DH(-) error model of a manipulator. The method is a hybrid scheme comprised of the Simulated Annealing (SA) algorithm and a local solver/optimizer and it conducts a statistical analysis on the estimates of a given error parameter that is indicative of its relevance. For the type of industrial robots used in this dissertation, we made note that calibrating the home position only is sufficient to attain adequate results for most robotics applications. Hence, we put forward for consideration of a yet simpler calibration model; the DH(-)(-) model. We employ the Trust Region (TR) method to minimize the objective functions (solve for the error parameters of the simplified error models) of both frameworks (3DCAL and 1DCAL). We also compare the performance of the proposed methods to that of a state-of-the-art commercial system (Motocal) using the same materials, data and internationally recognized performance standards. Our experimental results suggest that our methods are more robust and yield better results compared to that of MotoCal.

Committee:

Raul Ordonez, Ph.D. (Committee Chair); Russell Hardie, Ph.D. (Committee Member); John Loomis, Ph.D. (Committee Member); Ruihua Liu, Ph.D. (Committee Member)

Subjects:

Engineering; Robotics

Keywords:

Kinematic Calibration; Optimization; Simulated Annealing; Trust Region; CompuGauge; MotoCal; Industrial Robots; Yaskawa Motoman Robotics Inc

Graber-Tilton, AlexanderElements of Control for a Quadruped Robot
Master of Sciences (Engineering), Case Western Reserve University, 2016, EMC - Mechanical Engineering
Repairs and redesigns of components were done on the quadruped robot “Puppy” in order to bring it back into working order. A control system was derived from Cruse's method for a cat as well as LegConNet, which was derived from insects, and was initially tested using simulation. The control system was implemented on “Puppy” using a low-level custom controller board that I helped to design. Experiments showed robust air-walking gaits even in response to disturbances. However, difficulty in tuning parameters stymied attempts at ground walking in simulation and on the physical robot. The concept of a Zero-Moment Line (ZML) is also introduced, which is a 3D expansion on the Zero-Moment Point. The Zero-Moment Line is used as part of the control for a different quadruped robot in simulation. The ZML quadruped was tested on three types of terrain of increasing complexity, with the control displaying stability despite non-planar contact points.

Committee:

Roger D. Quinn (Advisor); Richard J. Bachmann (Committee Member); Gregory S. Lee (Committee Member)

Subjects:

Mechanical Engineering; Robotics

Keywords:

Robotics; Quadruped; Zero Moment Line; Zero Moment Point; ZML; ZMP; Control

Horchler, Andrew de SalleDesign of Stochastic Neural-inspired Dynamical Architectures: Coordination and Control of Hyper-redundant Robots
Doctor of Philosophy, Case Western Reserve University, 2016, EMC - Mechanical Engineering
Effective control of soft and hyper-redundant devices, such as worm-like robots, requires many degrees of freedom to be coordinated while adapting the sequential pattern of activity based on sensory feedback. A striking feature of biological pattern generators is their ability to respond immediately to multi-sensory perturbations by modulating the dwell time at a particular phase of activity without disrupting overall coordination. This dissertation presents new mathematical tools for the design and analysis of a dynamical architecture that can be used to responsively coordinate many degrees of freedom: stable heteroclinic channels (SHCs). For SHC cycles, the addition of stochastic noise results in oscillation with a regular mean period. A new soft robot, Compliant Modular Mesh Worm, which utilizes individually actuated segments to produce peristaltic locomotion, has been constructed as a platform to evaluate SHC control. The robot's modular mesh allows components to be easily interchanged to vary stiffness. Experiments were performed to characterize the actuated mesh and study how the interaction between friction, compliance, and the precision of segment control impacts locomotion performance. A real time SHC controller that allows predictable noise-driven variability of the robot's locomotion pattern was developed and evaluated. These results will be useful for the design and control of future peristaltic devices.

Committee:

Roger Quinn (Advisor); Hillel Chiel (Advisor); Joseph Mansour (Committee Member); Cenk Cavusoglu (Committee Member)

Subjects:

Biology; Biomechanics; Engineering; Mechanical Engineering; Neurosciences; Robotics; Robots

Keywords:

robot, biological inspiration, worm, earthworm, peristalsis, locomotion, soft robotics, compliant, modular, mesh, computational neuroscience, stochastic, noise, SDE, SHC, stable heteroclinic channels, simulation, pattern generation, dynamics

Baxi, Hemant K.Teleoperative Control Plus Simulation and Analysis of Walking for the DARwIn-OP Humanoid Robot
Master of Science (MS), Ohio University, 2016, Mechanical Engineering (Engineering and Technology)
The thesis attains the objective of developing a teleoperative system for controlling the humanoid robot DARwIn-OP. The user interface and the hardware is installed and tested. The idea behind developing a teleoperative robot is to use the robot in times of emergency and other major crises without endangering human life. The hardware developed used Bluetooth technology and the user interface was developed using Android Programming Environment. Code is developed to make the robot work by inputing command using the tablet running on Android. The other objective of analyzing the human walk and a robot walk is also attained. Hip joint, Knee joint, Ankle joint are compared for a human walk with respect to joint angle, joint angular velocity and joint angular acceleration. In order to make DARwIn-OP walk more energy efficient it is proposed to use the ZMP method with Genetic algorithm for optimizing the Gait parameters. Darwin-OP has a programmable walking controller to help it locomote while in soccer mode. This controller generates a sinusoid for lateral body motion. It also generates a step period to help it move forward. The walk path generated from the controller appears to create short and choppy steps for Darwin-OP [33]. A new method for walking gait generation for Darwin-OP is proposed using ZMP and Genetic algorithm for optimizing the walking gait of Darwin-OP. The ZMP method is able to generate a more stable walk path with longer strides. [34].

Committee:

Roberts Willams , II (Advisor)

Subjects:

Engineering; Mechanical Engineering

Keywords:

Teleoperative control; Darwin-OP;Robotics;Humanoid

Katbab, AbdollahThree-dimensional torso model with muscle actuators /
Doctor of Philosophy, The Ohio State University, 1983, Graduate School

Committee:

Not Provided (Other)

Subjects:

Engineering

Keywords:

Robotics;Manipulators;Muscles

Schepelmann, AlexanderIdentification & Segmentation of Lawn Grass Based on Color & Visual Texture Classifiers
Master of Sciences (Engineering), Case Western Reserve University, 2010, EMC - Mechanical Engineering
CWRU Cutter is an autonomous lawnmower which can reflexively avoid obstacles. While LIDAR was previously used by the robot to determine obstacle locations, the sensor’s price makes its inclusion in commercial versions prohibitively expensive. Cameras can provide similar information at drastically reduced cost, but useful information must first be extracted from incoming images. This can be computationally expensive. Additionally, vision-based methods can be highly sensitive to changing lighting conditions. This thesis presents a method to identify grass based on color and visual texture classifiers for use in an outdoor environment. Neighborhood-based color measurements are calculated using the HSL color model and texture measurements are based on edge-detection and quantified via computationally inexpensive first and second order statistics. Individual measurements are then combined to create a binary representation of mowable terrain in an image. Performance is quantified by measuring recognition performance on a set of sample neighborhoods that contains common backyard obstacles.

Committee:

Roger D. Quinn, PhD (Committee Chair); Francis Merat, PhD (Committee Member); Michael S. Branicky, ScD (Committee Member)

Subjects:

Computer Science; Engineering; Mechanical Engineering; Robots

Keywords:

Computer vision; texture; grass identification; autonomous vehicles; autonomous lawnmower; robotics

GHAFFARI, MASOUDPERCEPTION-BASED CONTROL FOR INTELLIGENT SYSTEMS
PhD, University of Cincinnati, 2006, Engineering : Industrial Engineering
Intelligent systems theory tries to study the most amazing feature of living creatures: intelligence. One active research area with many promising applications is autonomous navigation of unmanned vehicles which relies heavily on intelligent systems theory. The purpose of this dissertation is to apply an ambiguous concept in intelligent systems, called perception, in robot navigation. Several approaches have been used to model perception for robot navigation. A learning framework, equipped with a perception-based task control center, has been proposed. A statistical approach for uncertainty modeling has been investigated as well. In addition, a spatial knowledge model was used to model robot navigation. Finally, an optimization approach toward perception was used to model robot design and navigation. Several case studies of robot design will be presented. An unmanned ground vehicle, called the Bearcat Cub, was designed and developed for the Intelligent Ground Vehicle Competition (IGVC). This robot was used to demonstrate spatial knowledge modeling. In another design, a soil sampling survey robot was developed to measure the soil strength in remote areas. And finally, the design and development of a snow accumulation prevention robot will be presented. This autonomous robot can prevent accumulation of snow in areas such as driveways and small parking lots. The implementation of unique hardware and software systems in several robotic systems, as well as promoting a multifaceted view of perception modeling, are significant contributions made by this dissertation. The proposed framework uses optimization approach; it has learning capability, and is able to handle uncertain situations that are common in robot navigation.

Committee:

Ernest Hall (Advisor)

Subjects:

Engineering, Industrial

Keywords:

perception-based control; robotics; perception optimization

Joseph, Sharon A.Collective Path Planning by Robots on a Grid
MS, University of Cincinnati, 2010, Engineering : Computer Engineering

Planning plays a key role in any level of computation and problem solving. Given the problem statement and having decided on the goal, critical analysis and strong heuristics greatly impact the outcome of the action taken. While problem solving by default demands high precision and concentration, the level of uncertainty involved in the environment where the problem is solved is of significant importance. In this thesis we address the problem of traversing all the cells of a grid by a collection of cooperating robots. Several factors such as static/dynamic obstacles, nature of the terrain and natural factors elevate the uncertainty of the actual outcome. With the increasing amount of research into both static and dynamic environments, the challenges to be faced in the domain of collaborative robotics are still too many to enumerate. Several areas of artificial intelligence are still addressing these issues and this thesis addresses one problem for cooperating robots.

The primary goal of this thesis is to generate intelligent paths for a collection of robots in an environment with dynamically changing obstacles. Many existing approaches have addressed the problem in the context of a global camera or GPS system providing positional information to each robot. Our approach seeks to solve this problem in the context of robots getting their location information from a visible grid covering the terrain. The terrain is divided into a well-spaced grid and robots are challenged to visit every cell in the grid in the shortest period of time while overcoming starvation, avoiding deadlocks and detecting dynamic obstacles. All of their spatial knowledge is derived from the cell boundaries on the grid that they cross. This formulation with marked grid boundaries calculates paths, taking both global and local states of all the robots into consideration. Factors such as repeatedly visiting a cell, overlapping paths generated by two robots, and travel-time cost estimations are considered significant in calculating the most effective and intelligent path. The individual path generated by each robot is in response to the obstacles that were encountered during the executions of the path traversals.

The algorithm thus developed has been successfully tested with real robots in a laboratory setting. Robots with individual start points visited all the cells in the two dimensional grid. The overall execution time of the algorithm differed with the velocity, the nature of the terrain, and the relative start points. Interesting observations were made such as task sharing, resource utilization, and visiting the nearby cells rather than waiting for other robots to travel far in visiting those cells. The execution time was comparatively less when robots initiated with start points subjected to lower chances of starving, mutual exclusion, respecting better performing robots while avoiding accidents, and building global information from local information. The overall performance of the algorithm is analyzed and discussed in this thesis.

Committee:

Raj Bhatnagar, PhD (Committee Chair); John Schlipf, PhD (Committee Member); Karen Davis, PhD (Committee Member)

Subjects:

Computer Science

Keywords:

Collective Path Planning;Multi agent coordination;Robotics

Stewart, Austin M.The Militant Gardener
Master of Fine Arts, The Ohio State University, 2012, Art
Art actions, objects, writing, documents and installations are the forms used to examine human nature through the lenses of ecological crises and militancy. The artwork attempts to sharpen the viewer’s awareness of social mechanics of our species and challenge the viewer to consider solutions to seemingly intractable disputes that mesh well with our nature. The inherently dangerous nature of many of the works makes them impossible for an audience to experience directly in a gallery. The desire to present them as living works of art in a gallery, in contrast to documentation of a past event, required a re-examination of the relationship between the object and its documentation. I have come to the conclusion that all of the ephemera – videos, writing, flyers, performances – create a world for the art object and allow for communication between the world of the art object and our world.

Committee:

Amy Youngs, MFA (Advisor); Matthew Lewis, PhD (Committee Member); Kenneth Rinaldo, MFA (Committee Member)

Subjects:

Art Criticism

Keywords:

Art;New Media; Robotics; Militant; Seed Bomb; Virtual Reality; Husbandry; Terrorism

Leung Sem Tsuen, Henri GerardSelf-organized Construction of Spatial Structures by Swarms of Autonomous Mobile Agents
MS, University of Cincinnati, 2003, Engineering : Electrical Engineering
This thesis reports on two systems where very simple, non-communicating mobile agents in a cellular (lattice) environment use purely local rules to construct two different kinds of structures. In the first system, agents construct connected structures from initially randomly distributed building blocks. The effect of block density on the final structure is studied, demonstrating a percolation-like phase transition: Low block densities lead to the formation of small, disconnected structures but a single connected structure emerges abruptly beyond a critical density. The empirical study of the structure at the transition point shows scaling behavior, providing strong evidence for criticality. We also demonstrate that a simple change of rules can dramatically change the phase transition effect. The results have implications for the self-organized construction of complex structures by swarms. In the second system, agents construct walled enclosures around a number of non-mobile nodes which possibly represent resource locations or sites / items of interest. The walled enclosure is constructed in two stages: 1) A pheromone template is first built and maintained by the agents, and 2) A single connected wall is built that fully surrounds all the nodes in the environment. We show that the shape of the enclosure produced can be predicted approximately in cases where the nodes form a convex shape. We also show that the shape can be “guided” systematically to a limited degree.

Committee:

Dr. Ali A. Minai (Advisor)

Keywords:

self-organized construction; swarm intelligence; percolation; swarm-based robotics

Buenrostro-Nava, Marco T.Characterization of GFP Gene Expression Using an Automated Image Collection System and Image Analysis
Doctor of Philosophy, The Ohio State University, 2002, Horticulture and Crop Science

Automated systems can be used to facilitate continual collection of biological information from a large number of samples over long periods of time. The use of an automated system and image analysis would allow semi-continual monitoring and non-invasive quantification of the green fluorescent protein (GFP) expression and would therefore provide a better assessment of the levels of gfp gene expression than monitoring GFP at large time intervals. The main aim of this research was to monitor and quantify the expression of the gfp gene from the jellyfish (Aequorea victoria) and in vitro plant growth over time using an automated image acquisition system in combination with image analysis.

The system, developed over the course of this work, consisted of a computer controlled two-dimensional positioning table and a charged-coupled device (CCD) camera mounted on a stereomicroscope equipped with a GFP fluorescence detection system. The image collection system was placed in a horizontal laminar air flow hood to provide an aseptic environment for monitoring in vitro cultures.

In order to compare the pattern of expression of a soluble and an endoplasmic reticulum-targeted gfp gene, images of lima bean (Phaseolus lunatus L.) cotyledons transiently expressing the two different gfp genes, were collected every 30 min for 38 h. Time-lapse animations together with quantification of transient GFP expression using image analysis, showed that expression of the cytoplasmic soluble gfp gene was detected as early as 4 h after bombardment and reached a maximum at 24 h after bombardment. Expression of the endoplasmatic reticulum-targeted gfp gene was first observed 8 h after bombardment and reached its maximum expression after 24 h.

The pattern of GFP expression, driven by the soybean lectin and 35S promoters, was monitored every 12 h for 28 d during somatic embryo development using the automated image collection system. Gene expression was then quantified using image analysis. Quantitative analysis revealed that, even though the lectin: gfp construction showed low levels of expression during early stages of development, expression levels eventually reached levels similar to those recorded from the 35S: gfp construction. Embryos with gfp under the regulatory control of the lectin promoter showed a peak of expression 47 days after embryo development, while GFP expression driven by the 35S promoter gradually increased throughout embryo development. Time-lapse animations were useful in characterization of gfp expression, and revealed a high variability in levels of gfp expression driven by the 35S promoter.

Southern analysis showed the presence of multiple copies of the introduced plasmids for clones generated using particle bombardment. The copy number of clones containing the lectin: gfp construction, was not correlated with levels of gfp expression; however, a high copy number may have led to reduced levels of GFP expression of a clone containing the 35S: gfp construction.

Committee:

John Finer (Advisor)

Subjects:

Biology, Molecular

Keywords:

Plant transformation; Analysis of gene expression; Image analysis; Robotics; Green fluorescent protein; Lima beans; Soybean; Wheat; Arabidopsis

Taylor, Brian KyleTRACKING FLUID-BORNE ODORS IN DIVERSE AND DYNAMIC ENVIRONMENTS USING MULTIPLE SENSORY MECHANISMS
Doctor of Philosophy, Case Western Reserve University, 2012, EMC - Mechanical Engineering

The ability to locate odor sources in different types of environments (i.e. diverse) and environments that change radically during the mission (i.e., dynamic) is essential. While many engineered odor tracking systems have been developed, they appear to be designed for a particular environment (e.g., strong or low flow). In field conditions, agents may encounter both. Insect olfactory orientation studies show that several animals can locate odor sources in both high and low flow environments, and environments where the wind vanishes during tracking behavior. Furthermore, animals use multi-modal sensing, including olfaction, vision and touch to localize a source.

This work uses simulated and hardware environments to explore how engineered systems can maintain wind-driven tracking behavior in diverse and dynamic environments. The simulation uses olfaction, vision and tactile attributes to track and localize a source in the following environments: high flow, low flow, and transition from high to low flow (i.e., Wind Stop). The hardware platform tests two disparate tracking strategies (including the simulated strategy) in an environment that transitions from strong to low flow. Results indicate that using a remembered wind direction post wind-shutoff is a viable way to maintain wind-driven tracking behavior in a wind stop environment, which can help bridge the gap between high flow and low flow strategies. Also, multi-modal sensing with tactile attributes, vision and olfaction helps a vehicle to localize a source. In addition to engineered systems, the moth Manduca sexta is challenged to track in the following environments: Wind and Odor, Wind Stop, Odor and No Wind, No Odor and No Wind to gain a better understanding of animal behavior in these environments. Results show that contrary to previous studies of different moth species, M. sexta does not generally maintain its wind-driven tracking behavior post-wind shutoff, but instead executes a stereotyped sequence of maneuvers followed by odor-modulated undirected exploration of its environment. In the Odor and No Wind environment, animals become biased towards the area of the arena where odor is located compared to the No Odor and No Wind environment. Robot and animal results are compared to learn more about both.

Committee:

Roger Quinn, PhD (Committee Chair); Mark Willis, PhD (Committee Member); Joseph Mansour, PhD (Committee Member); Michael Branicky, Sc.D. (Committee Member)

Subjects:

Aerospace Engineering; Animal Sciences; Biology; Mechanical Engineering; Robotics

Keywords:

odor tracking; chemical plume tracing; odor guided navigation; biologically inspired robotics; insect olfactory orientation; diverse and dynamic environments; multi-modal sensing

Buchner, Helmut JosefControl of robot manipulators on task oriented surfaces by nonlinear decoupling feedback and compensation of certain classes of disturbances /
Doctor of Philosophy, The Ohio State University, 1986, Graduate School

Committee:

Not Provided (Other)

Subjects:

Engineering

Keywords:

Robots;Manipulators ;Feedback control systems;Robotics

Shakeel, AmlaanService robot for the visually impaired: Providing navigational assistance using Deep Learning
Master of Science, Miami University, 2017, Computational Science and Engineering
Assistive technology helps improve the day to day activities for people with disabilities. One of the methods utilized by assistive technologists employs the use of robots. These are called service robots. This thesis explores the idea of a service robot for the visually impaired to assist with navigation and is inspired by the use of guide dogs. The focus of this thesis is to develop a robot to achieve autonomous indoor navigation using computer vision to identify image based goals in an unfamiliar environment. The method presented in this thesis utilizes a deep learning framework, called Faster R-CNN, to train a computer to classify and localize exit signs in real time. A proof of concept is presented using NVIDIA Jetson, and TurtleBot, a robot kit, which runs a robot software development framework Robot Operating System (ROS). The model is trained successfully using Faster R-CNN and is validated. The model is used for real-time object classification on the prototype robot.

Committee:

Yamuna Rajasekhar (Advisor); John Femiani (Committee Member); Donald Ucci (Committee Member)

Subjects:

Computer Science; Electrical Engineering; Robotics

Keywords:

Assistive technology; Deep learning; Robotics; Indoor navigation; Computer vision; Robot Operating System; ROS; Caffe; Faster R-CNN; Convolutional Neural Networks; CNN; Microsoft Kinect; Service robots; visually impaired; mobility; depth perception

Bebek, OzkanROBOTIC-ASSISTED BEATING HEART SURGERY
Doctor of Philosophy, Case Western Reserve University, 2008, Systems and Control Engineering

Coronary heart disease is a leading cause of death in the USA. A promising treatment option for this disease is off-pump coronary artery bypass graft (CABG) surgery as the artery grafting is done without stopping the heart. In the robotic assisted-surgery concept the surgeon views the surgical scene on a video display and operates on the heart as if it were stationary while the robotic system actively compensates for the motion of the heart. With the proposed system concept, the CABG surgery will be possible without using passive stabilizers, and the hospitalization time and cost of the operation will be decreased.

In this dissertation intelligent robotic tools for assisting off-pump (beating heart) CABG surgery are presented. Most important aspects of such a robotic system are accurately measuring and predicting the heart motion as they are instrumental in canceling the relative motion between the heart surface and surgical tools attached to the robotic manipulators. The proposed control algorithm contributes to the field by using biological signals in the estimation of heart's future motion for active relative motion canceling. Also a novel contact position sensor is developed to measure the position of the beating heart and a preliminary noise characterization for the future sensor system implementation is presented.

Committee:

Murat Cavusoglu (Advisor)

Keywords:

bypass surgery; flexible structures; medical robotics; motion canceling; motion sensing; real time tracking; sensor fusion; whisker-like.

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