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Khalili, MohsenDistributed Adaptive Fault-Tolerant Control of Nonlinear Uncertain Multi-Agent Systems
Doctor of Philosophy (PhD), Wright State University, 2017, Engineering PhD
The research on distributed multi-agent systems has received increasing attention due to its broad applications in numerous areas, such as unmanned ground and aerial vehicles, smart grid, sensor networks, etc. Since such distributed multi-agent systems need to operate reliably at all time, despite the possible occurrence of faulty behaviors in some agents, the development of fault-tolerant control schemes is a crucial step in achieving reliable and safe operations. The objective of this research is to develop a distributed adaptive fault-tolerant control (FTC) scheme for nonlinear uncertain multi-agent systems under intercommunication graphs with asymmetric weights. Under suitable assumptions, the closed-loop system's stability and leader-follower cooperative tracking properties are rigorously established. First, a distributed adaptive fault-tolerant control method for nonlinear uncertain first-order multi-agent systems is developed. Second, this distributed FTC method is extended to nonlinear uncertain second-order multi-agent systems. Next, adaptive-approximation-based FTC algorithms are developed for two cases of high-order multi-agent systems, i.e., with full-state measurement and with only limited output measurement, respectively. Finally, the distributed adaptive fault-tolerant formation tracking algorithms for first-order multi-agent systems are implemented and demonstrated using Wright State's real-time indoor autonomous robots test environment. The experimental formation tracking results illustrate the effectiveness of the proposed methods.

Committee:

Xiaodong Zhang, Ph.D. (Advisor); Kuldip Rattan, Ph.D. (Committee Member); Pradeep Misra, Ph.D. (Committee Member); Yongcan Cao, Ph.D. (Committee Member); Raul Ordonez, Ph.D. (Committee Member); Mark Mears, Ph.D. (Committee Member)

Subjects:

Electrical Engineering; Engineering

Keywords:

Fault-Tolerant Control; Adaptive Control; Multi-Agent Systems; Nonlinear Uncertain Systems; Formation Control; Learning Systems; Cooperative Tracking; Leader-Follower Consensus; Asymmetric Communication Graphs; Fault Diagnosis; Mobile Robots

ALHAJ ALI, SOUMA MAHMOUDTECHNOLOGIES FOR AUTONOMOUS NAVIGATION IN UNSTRUCTURED OUTDOOR ENVIRONMENTS
PhD, University of Cincinnati, 2003, Engineering : Industrial Engineering
Robots have been used in manufacturing and service industries to improve productivity, quality, and flexibility. Robots are usually mounted on a fixed plate, or on rails, and can move in a limited manner. The success of robots in these environments encourages the use of mobile robots in other applications where the environments are not structured, such as in outdoor environments. This dissertation presents the development of an autonomous navigation and obstacle avoidance system for a Wheeled Mobile Robot (WMR) operating in unstructured outdoor environments. The algorithm produces the robots path positioned within the road boundaries and avoids any fixed obstacles along the path. The navigation algorithm was developed from a feedforward multilayer neural network. The network used a quasi-Newton backpropagation algorithm for training. Proportional-plus-derivative computed-torque, proportional-plus-integral-plus-derivative computed-torque, digital, and adaptive controllers were developed to select suitable control torques for the motors, which cause the robot to follow the desired path from the navigation algorithm. Simulation software permitting easy investigation of alternative architectures was developed by using Matlab and C++. The simulation software for the controllers was developed for two case studies. The first case study is the two-link robot manipulator, and the second is a navigation controller for the WMR. The simulation software for the WMR navigation controller used the Bearcat III dynamic model, developed in this dissertation. Simulation results verify the effectiveness of the navigation algorithm and the controllers. The navigation algorithm was able to produce a path with a small mean square error, compared to the targeted path, which was developed by using an experienced driver. The algorithm also produced acceptable results when tested with different kinds of roads and obstacles. The controllers found suitable control torques, permitting the robot to follow these paths. The digital controller produced the best results. The significance of this work is the development of a dynamic system model and controllers for WMR navigation, rather than robot manipulators, which is a new research area. In addition, the navigation system can be utilized in numerous applications, including various defense, industrial and medical robots.

Committee:

Dr. Ernest L. Hall (Advisor)

Subjects:

Engineering, Industrial

Keywords:

wheeled mobile robots; autonomous navigation in unstructured environments; PD-computed-torque controller; PID computed-torque controller

Singh, DaljeetPath Planning and Evolutionary Optimization of Wheeled Robots
Master of Science in Electrical Engineering, Cleveland State University, 2013, Fenn College of Engineering
Probabilistic roadmap methods (PRM) have been a well-known solution for solving motion planning problems where we have a fixed set of start and goal configurations in a workspace. We define a configuration space with static obstacles. We implement PRM to find a feasible path between start and goal for car-like robots. We further extend the concept of path planning by incorporating evolutionary optimization algorithms to tune the PRM parameters. The theory is demonstrated with simulations and experiments. Our results show that there is a significant improvement in the performance metrics of PRM after optimizing the PRM parameters using biogeography-based optimization, which is an evolutionary optimization algorithm. The performance metrics (namely path length, number of hops, number of loops and fail-rate) show 34.91%, 23.18%, 52.21% and 21.21% improvement after using optimized PRM parameters. We also experimentally demonstrate the application of path planning using PRM to mobile car-like robots.

Committee:

Dan Simon, PhD (Committee Chair); Nigamanth Sridhar, PhD (Committee Member); Chansu Yu, PhD (Committee Member)

Subjects:

Computer Engineering; Electrical Engineering; Engineering; Robotics

Keywords:

Proababilistic roadmap methods; Biogeography-based optimization; PRM; BBO; Path planning; Mobile robots

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

MURTY, VIDYASAGAROBSTACLE AVOIDANCE IN AN UNSTRUCTURED ENVIRONMENT FOR THE BEARCAT
MS, University of Cincinnati, 2003, Engineering : Industrial Engineering
The Center for Robotics Research at University of Cincinnati does extensive research on mobile robot technologies. The Center developed the Bearcat, an autonomous unmanned vehicle (AUV). The Bearcat can autonomously navigate and avoid a limited configuration of obstacles in a structured environment. This research provides a solution for the Bearcat to navigate autonomously in an unstructured environment. A simple wandering algorithm was developed to avoid obstacles in an unstructured environment. The algorithm uses feedback from a laser scanner. It filters the data received, identifies potential obstacles and accordingly changes the path of the robot to avoid the obstacles based on their configuration. This is achieved by sending explicit motion commands to the motion controller which moves the robot. The algorithm was successfully tested to avoid obstacles in an unstructured environment with certain limitations. The algorithm was also used by the Bearcat in the Autonomous Challenge event at the 11th annual International Ground Vehicles Competition (IGVC) organized by the Association of Unmanned Vehicle Systems International (AUVSI) enabling it to win the fifth place in the competition. The research provides a starting point to build and develop a robust algorithm to address complex, real life issues where the robots have to generate alternate paths to avoid obstacles in a dynamic and unstructured environment.

Committee:

Dr. Ernest Hall (Advisor)

Subjects:

Engineering, Industrial

Keywords:

autonomous ground vehicles; obstacle avoidance; unstructured environment; mobile robots

FRANCIS, SHINCEREMOTE ADMINISTRATION OF AN AUTONOMOUS GUIDED VEHICLE THROUGH WEB BASED WIRELESS INTERFACES
MS, University of Cincinnati, 2003, Engineering : Industrial Engineering
Motion control is one of the most critical factors in the design of autonomous vehicles such as mobile robots. Bearcat III is an autonomous vehicle designed by the student at the Center for Robotics Research at the University of Cincinnati. The data transfer between the motion controller and the computer on Bearcat III is via serial port interface. This method is inflexible, sluggish and dated. A new motion control solution that uses a Galil DMC-2130 motion controller with a Galil ICM 1900 as the interconnect board is proposed. The new motion control system uses a DC brush less servo motor with encoders for feedback control. The choice of amplifier depends up on the choice of the motor type. This forms a closed loop feedback control system. The communication between motion controller (DMC-2130) and the central computer is achieved using Ethernet technology. This facilitates the use of Internet communication protocols and wireless communication standards to control the robot remotely. The new motion control system thus helps to control the robot via Internet and without physically present near the robot. The systems will be tested on the new robot, Bearcat cub, built by the students of the Center for Robotics Research. The significance of this work is in the increased understanding of motion control system for robot control and the synergetic combination of autonomous control of a robot and Internet and wireless communication standards in the field of defense and medicine.

Committee:

Dr. Ernest Hall (Advisor)

Subjects:

Engineering, Industrial

Keywords:

robotics; mobile robots; TCP/IP; wireless networking

Sun, Wei3-D collision detection and path planning for mobile robots in time varying environment
Master of Science (MS), Ohio University, 1989, Electrical Engineering & Computer Science (Engineering and Technology)

3-D collision detection and path planning for mobile robots in time varying environment

Committee:

M. Celenky (Advisor)

Keywords:

3-D Collision Detection; Path planning; Mobile robots; Time Varying Environment

Carter, Brian EdwardOmni-directional locomotion for mobile robots
Master of Science (MS), Ohio University, 2001, Mechanical Engineering (Engineering)
In this Thesis, a brief overview of mobile robots and omni-directional robots is presented, as well as a detailed history of the RoboCup competition. The player robot design process undertaken by the Ohio University Mechanical Engineering department led by the author) is discussed in detail, and the inverse kinematic equations and dynamic equations of motion are derived. These dynamic equations were then used to create two Simulink simulations, the simple and complex dynamic models. A third simulation was created to compensate for the slipping disturbances in the wheel motivated by initial experimental work. The most accurate of the simulations (the third, dubbed the Slip Simulation) was then compared with the experimental data.

Committee:

Robert Williams, II (Advisor)

Subjects:

Engineering, Mechanical

Keywords:

Mobile Robots; Omni-Directional Robots; RoboCup Competition; Dynamic Equations; inverse kinematic equations; Simulink simulations; slipping disturbances

Paul, Suresh LazarusCurvilinear Traverse Generation Module for an AGV
MS, University of Cincinnati, 2003, Engineering : Industrial Engineering
The purpose of this thesis is to study the point-to-point navigation of an AGV in an unstructured environment. The problem under consideration is to compute the minimum distance of traverse of the AGV through a set of known points, where the routing through these points would determine the efficacy of the AGV to navigate the domain. The criticality of this study is to enhance the response of the AGV in exploring a specific domain. This response time is vital for minimizing power and fuel requirement of the AGV. The response of the AGV to any change in a straight-line direction is associated with the close down – resume characteristics. A close down-resume characteristic is a kind of straight-line operation of a vehicle when it has to stop in order to change the direction of its course. Hence, the number of target points in the domain would dictate the number of times that the AGV must stop and change its course. This routing is compared with a curvilinear path, which is formulated by generating a curve through the same target points. Since the curve has less change in directional properties compared to a straight-line, the AGV can respond without a close down-resume characteristics and perform a uniform velocity traverse, thereby, reducing the time for traverse through the domain. This study focuses on providing different methods of generating curves in a domain with a given set of target control points. The methods formulated in this study are curve-fitting using indexing reference points, which is a geometrical construction of a curvilinear path, Voronoi curve generation method, which uses the Voronoi principle for curve generation, and a hybrid curve generation method, which is a combination of the above two methods. The results of this study show the time required to travel in any area, given the optimum details of the terrain. There is a definite reduction of the time of travel by the AGV in comparison with the other navigation modules. It also proves to be safer to account for the maximum travel time for the AGV to explore, as its operation is restricted to fuel/power consumption. Further, the AGV can stop at any point on its travel and negotiate a reverse traverse back to the start point, if necessary. The significance of this study is to understand and interpret the higher flexibility of the vehicle to explore the domain by sending feedback on its surroundings in a curvilinear path. The constraint for navigation is avoiding collision with any significant obstacle in its track. The AGV is pre-functioned with the obstacle avoidance operational mode, and must be able to give the exact time required for the travel to be safe as required for its functionality.

Committee:

Dr. Ernest L. Hall (Advisor)

Keywords:

curvilinear traverse; navigational algorithm; mobile robots; AGV

Alsaedi, Rusul JabbarON THE MUTUAL VISIBILITY OF FAT MOBILE ROBOTS
MS, Kent State University, 2016, College of Arts and Sciences / Department of Computer Science
Given a set of n >= 1 autonomous, anonymous, history-oblivious, silent, and possibly disoriented mobile robots operating following Look-Compute-Move cycles in the Euclidean plane, we consider the fundamental problem of providing mutual visibility for them, i.e., the robots must reposition themselves to reach a configuration in finite time without collisions where they all see each other. This problem arises under obstructed visibility where a robot can not see another robot if there lies a third robot on the line segment connecting their positions. This problem is important since it provides a basis to solve many other problems under obstructed visibility, and it has applications in many scenarios including coverage, intruder detection, etc. The literature on this problem assumed that the robots are dimensionless points, i.e., they occupy no space. However, this assumption can be easily refuted. For example, in reality, robots are not dimensionless, but they have a physical extent. Therefore, in this thesis, we initiate the study of the mutual visibility problem for the robots with extents. We address this problem in the recently proposed robots with lights model, where each robot is equipped with an externally visible persistent light that can assume colors from a fixed set of colors. This model corresponds to the classical oblivious robots model when the number of colors in the set is 1. In particular, we first develop a deterministic algorithm that provides mutual visibility for robots with extents of unit disc size avoiding collisions using only 4 colors in the color set. Note that this algorithm works for fat robots under the fully synchronous and semi-synchronous settings. We then present a faster algorithm that solves this problem in O(n) rounds in the fully synchronous setting.

Committee:

Gokarna Sharma (Advisor); Feodor Dragan (Committee Member); Hassan Peyravi (Committee Member)

Subjects:

Computer Science

Keywords:

Distributed Algorithms, Autonomous Mobile Robots, Fat Robots, Obstructed Visibility, Robots with Lights Model, Run-time, Configuration, Convex Hull, Mutual Visibility, Collisions

Pech, Thomas JoelA Deep-Learning Approach to Evaluating the Navigability of Off-Road Terrain from 3-D Imaging
Master of Sciences (Engineering), Case Western Reserve University, 2017, EECS - Computer and Information Sciences
This work investigates a strategy for evaluating the navigability of terrain from 3-D imaging. Labeled training data was automatically generated by running a simulation of a mobile robot nai¨vely exploring a virtual world. During this exploration, sections of terrain were perceived through simulated depth imaging and saved with labels of safe or unsafe, depending on the outcome of the robot's experience driving through the perceived regions. This labeled data was used to train a deep convolutional neural network. Once trained, the network was able to evaluate the safety of perceived regions. The trained network was shown to be effective in achieving safe, autonomous driving through novel, challenging, unmapped terrain.

Committee:

Wyatt Newman (Advisor); Cenk Cavusoglu (Committee Member); Michael Lewicki (Committee Member)

Subjects:

Computer Science; Robotics; Robots

Keywords:

Mobile robots, Autonomous Navigation, Machine Learning, Artificial Neural Networks, Terrain, Simulation, Training Data, Data Generation, Labeling, Classifiers, Convolutional Neural Networks, Point Clouds, Perception, Prediction, Artificial Intelligence

Henning, Timothy PaulDynamics and controls for an omnidirectional robot
Master of Science (MS), Ohio University, 2003, Mechanical Engineering (Engineering)
This thesis presents a brief overview of mobile robots and omni-directional motion. The design process of the Ohio University RoboCup robots is also explained in detail, along with recommended design changes for future robots. The forward and inverse kinematic equations are derived along with the dynamic equations of motion. These equations were then used to perform computer simulations and hardware experiments to evaluate and improve on the current performance of the robot. Hardware experiments were also done using a vision-based system. These results were then compared to the results of the hardware simulations completed with a tethered robot. Experiments were also run to show the effects of slippage as the speed of the robot is increased. The results show that the dynamic model used in Simulink properly represents the actual robot. They also show that some type of higher order path planning is needed in order for the robot to make smooth movements. In comparing the hardware experiments, the tethered robot shows a definite improvement in the speed and accuracy of the robot while completing predetermined patterns.

Committee:

Robert Williams, II. (Advisor)

Subjects:

Engineering, Mechanical

Keywords:

Mobile Robots; Omni-Directional Motion; RoboCup Robots; Inverse Kinematic Equations; Computer Simulations; Hardware Experiments; Vision-Based System; Tethered Robot; Predetermined Patterns

Cockrell, StephanieUSING THE XBOX KINECT TO DETECT FEATURES OF THE FLOOR SURFACE
Master of Sciences (Engineering), Case Western Reserve University, 2013, EECS - Electrical Engineering
This thesis examines the effectiveness of the Xbox Kinect as a sensor to identify features of the navigation surface in front of a smart wheelchair robot. Recent advances in mobile robotics have brought about the development of smart wheelchairs to assist disabled people, allowing them to be more independent. Because these robots have a human occupant, safety is the highest priority, and the robot must be able to detect hazards like holes, stairs, or obstacles. Furthermore, to ensure safe navigation, wheelchairs often need to locate and navigate on ramps. The results demonstrate how data from the Kinect can be processed to effectively identify these features, increasing occupant safety and allowing for a smoother ride.

Committee:

Greg Lee (Advisor); Frank Merat (Committee Member); Cenk Cavusoglu (Committee Member)

Subjects:

Electrical Engineering; Robotics

Keywords:

Kinect; robotics; obstacle detection; drivable surfaces; ramps; smart wheelchairs; mobile robots