Dissertations / Theses on the topic 'Global path planning'

The aim of the research project that is the subject of this thesis is to apply mathematical techniques, especially those in the area of operations research, to the problem of maritime minefield transit. We develop several minefield models applicable to different aspects of the minefield problem. These include optimal mine clearance, shortest time traversal and time constrained traversal. We hope the suite of models and tools developed will help make mine field clearance and traversal both safer and more efficient and that exposition of the models will bring a clearer understanding of the mine problem from a mathematical perspective. In developing the solutions to mine field models, extensive use is made of network path planning algorithms, particularly the Weight Constrained Shortest Path Problem (WCSPP) for which the current state-of-the-art algorithm is extended. This is done by closer integration of Lagrangean relaxation and preprocessing to reduce the size of the network. This is then integrated with gap-closing algorithms based on enumeration to provide optimal or near optimal solutions to the path planning problem. We provide extensive computational evidence on the performance of our algorithm and compare it to other algorithms found in the literature. This tool then became fundamental in solving various separate minefield models. Our models can be broadly separated into obstacle models in which mine affected regions are treated as obstacles to be avoided and continuous threat in which each point of space has an associated risk. In the later case, we wish to find a path that minimizes the integral of the risk along the path while constraining the length of the path. We call this the Continuous Euclidean Length Constrained Minimum Cost Path Problem (C-LCMCPP), for which we present a novel network approach to solving this continuous problem. This approach results in being able to calculate a global lower bound on a non-convex optimization problem.

Mestrado em Engenharia de Automação Industrial
Atlascar is a project developed in the Automation and Robotics laboratory at the Mechanical Department of the University of Aveiro, Portugal. It is used for research in autonomous navigation and for advanced driver assistance systems. The aim of this thesis is to develop a navigation system for path planning, which includes a graphical interface that allows the user to input a nal destination, with possible via points if needed. The application should be able to track the vehicle in real-time and output sequences of high level maneuvers along the mission. New hardware is also to be installed and con gured, namely a new server and a new GPS receiver, which requires an intervention on the previous setup of the Atlascar. The whole system is divided into three parts: Planner, Navigator and User interface. The planner module will be responsible for calculating the path and the instructions. The navigator module will be responsible for processing the data from the planner module ; communicating with a database, read and write values and acquiring data from the GPS. The user interface allows the user to input the desired destination by clicking on a map, this module also allows the user to: monitor the current location of the vehicle; view the path to the destination and it shows the instruction that needs to be done. This module also establishes a communication with the database. This module is optional because the system also works without a user interface, it simply allows the user to do it interactively and it allows motorization. If a wrong decision is made and the user follows a wrong path, the system will recalculate the mission and show a new path.
O Atlascar é um projeto desenvolvido no laboratório de automação e robótica, no departamento de Engenharia Mecânica da Universidade de Aveiro. Este veículo é utilizado para investigação em condução autónoma e sistemas avançados de apoio ao condutor. O objetivo desta dissertação é desenvolver um sistema de navegação para planeamento de rotas. Este sistema inclui uma interface gráfica que permite ao utilizador selecionar um destino, com pontos de passagem intermédios se assim for pretendido. A aplicação deve permitir monitorizar em tempo real o veículo e indicar as manobras que devem ser realizadas ao longo do percurso. Novo hardware ter a de ser instalado e configurado, nomeadamente um novo servidor e recetor GPS. Isto requer uma intervenção na configuração atual do Atlascar. O sistema está dividido em três partes: Planeador, Navegador e Interface Gráfica. O módulo do planeador é responsável por calcular os percursos e as manobras a realizar. O navegador é responsável pelo processamento dos dados vindos do planeador. Estabelece uma comunicação com uma base de dados de onde vai ler e escrever valores. Este módulo também será responsável por ler os valores vindos do GPS. A interface gráfica permite ao utilizador selecionar o destino pretendido, o que é feito clicando num mapa. Este módulo também permite monitorizar a localização do veículo, ver o percurso que irá ser realizado e apresenta a instrução a realizar. Este módulo também estabelece uma comunicação com uma base de dados. Este módulo é opcional porque o sistema também funciona sem uma interface visual, esta simplesmente permite ao utilizador fazê-lo de forma interactiva e também permite monitorização. Caso o utilizador escolha um percurso errado durante a viagem, o sistema recalcula a missão e apresenta um novo caminho.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2006.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (leaves 93-95).
With the advance in the fields of computer science, control and optimization, it is now possible to build aerial vehicles which do not need pilots. An important capability for such autonomous vehicles is to be able to generate their own path to navigate in a constrained environment and accomplish mission objectives, such as reaching waypoints in minimal time. To account for dynamic changes in the environment, perturbations, modeling errors and modifications in the mission scenario, the trajectory needs to be continuously re-optimized online based on the latest available updates. However, to allow for high update rates, the trajectory optimization problem needs to be simple enough to be solved quickly. Optimizing for a continuous trajectory of a dynamically-constrained vehicle in the presence of obstacles is an infinite-dimension nonlinear optimal control problem. Such a problem is intractable in real-time and simplifications need to be made. In this thesis, the author presents the mechanisms used to design a path-planner with real-time and long-range capabilities. The approach relies on converting the optimal control problem into a parameter optimization one whose horizon can be reduced by using a global cost-to-go function to provide an approximate cost for the tail of the trajectory.
(cont.) Thus only the short-term trajectory is being constantly optimized online based on a mixed integer linear programming formulation that accounts for the vehicle's performance. The cost-to-go function presented in this thesis has the feature to be tailored to both the environment and the vehicle's maneuvering capabilities. The author then implements and demonstrates a path-planner software based on the presented approach for a real unmanned helicopter, the Renegade, that flew within the DARPA SEC program. A full description of the capabilities and functions supported by the planner software are provided. Hardware-in-the-loop simulation results are provided to illustrate the performance of the system.
by Olivier Toupet.
S.M.

Automotive manufacturers are facing increasing pressure from legislative bodies and consumers to reduce fuel consumption and greenhouse gas emissions of vehicles. This has led to many automotive manufacturers starting production of Plug-in Hybrid Electric Vehicles (PHEV's) and Battery Electric Vehicles (BEV's). Another method that helps to reduce the environmental effect of transportation is EcoRouting. The standard Global Positioning System (GPS) navigation offers route alternatives between user specified origin and destination. This technology provides multiple routes to the user and focuses on reducing the travel time to reach to the destination. EcoRouting is the method to determine a route that minimizes vehicle energy consumption, unlike traditional routing methods that minimize travel time. An EcoRouting system has been developed as a part of this thesis that takes in information such as speed limits, the number of stop lights, and the road grade to calculate the energy consumption of a vehicle along a route. A synthesis methodology is introduced that takes into consideration the distance between the origin and destination, the acceleration rate of the vehicle, cruise speed and jerk rate as inputs to simulate driver behavior on a given route. A new approach is presented in this thesis that weighs the energy consumption for different routes and chooses the route with the least energy consumption, subject to a constraint on travel time. A cost function for quantifying the effect of travel time is introduced that assists in choosing the EcoRoute with an acceptable limit on the travel time required to reach the destination. The analysis of the EcoRouting system with minimum number of conditional stops and maximum number of conditional stops is done in this thesis. The effect on energy consumption with the presence and absence of road-grade information along a route is also studied. A sensitivity study is performed to observe the change in energy consumption of the vehicle with a change in acceleration rates and road grade. Three routing scenarios are presented in this thesis to demonstrate the functionality of EcoRouting. The EcoRouting model presented in this thesis is also validated against an external EcoRouting research paper and the energy consumption along three routes is calculated. The EcoRoute solution is found to vary with the information given to the variable acceleration rate model. The synthesis and the results that are obtained show that parameters such as acceleration, deceleration, and road grade affect the overall energy consumption of a vehicle and are helpful in determining the EcoRoute.
Master of Science

碩士
國立臺灣科技大學
自動化及控制研究所
100
Autonomous robots are widely used in various applications such as industrial, military, exhibition and home care. Dynamic path planning including obstacle avoidance in real-time is a critical issue for the success of mobile robots in the above dynamic environments. In recent years, most of researches focus on using local sensors to avoid dynamic obstacles. It performances well in obstacle avoidance, but is not an efficient way of goal-oriented system navigation. This thesis proposes a dynamic path planning system only using omni-directional camera on the ceiling. Based on the global view, background subtraction method is applied to detect a moving object and Kalman/Particle filter based on HSV (hue, saturation, and value) color space is used to track the moving object. Furthermore, this system integrates reduced visibility graph algorithm and parallel processing in path planning to reduce the computation time from 4115 ms to less than 200 ms in 457x357 cm2 work space. Finally, it navigates the mobile robot with closed loop control through the server-client model. Our experimental results show that the Particle Filter is not only more robust than Kalman Filter to the speed change of moving object but also has better performance during object occlusion and illumination changes. The results also demonstrate the effectiveness and efficiency of the proposed visual servoing system. The system successfully controls the motion of a robot to avoid dynamic obstacle of speed 200 mm/s and re-plans a new path in real-time when necessary. It also maintains the trajectory following error of less than 30 mm with the closed loop control.

碩士
淡江大學
機械與機電工程學系碩士班
96
The objective of this research is to develop a robotic mobility platform, which using Segway RMP 50 to demonstrate the optimum path planning under A* algorithm and a developed map. Segway RMP 50 is the principal platform in this research. The self-designed mechanical loading structured is installed on the RMP 50 to set up the notebook computer/webcam. The robot system is capable to install more sensors to detect the environmental information beside this robot. A client control system is developed to be a server by the webcam and laptop computer. The other users are able to watch the pc screen to find out the related environmental images by the internet from the developed server. The A* algorithm and a developed grid map are applied to let this robot be able to avoid obstacle and make an optimum path planning. The simulation results show that the Segway RMP 50 system is capable to make a simple movement planning and to calculate the length of the moving path. Finally, the robot system is demonstrated its ability of obstacle–avoidance and the optimum path planning by the A* algorithm.

碩士
國立臺灣科技大學
電機工程系
100
In recent years, an autonomous mobile robot is required for performing several different tasks, such as removal of hazardous mines, exploration of volcano, monitoring nuclear power plants, etc. In general, these tasks are in hazardous and populated environments. A mobile robot must be able to deal with unexpected changes in the environment and to perform complex assignments in a short period of time. In this work, the focus is to provide a method for a mobile robot to navigate safely in an unknown and dynamic environment. The proposed scenario is "Assistance and Rescue Disaster", where a mobile robot is used to steer through a hazardous site in search of victims, in order to provide them rescue or emergency assistance. The approach used is a hybrid of visual global path plan and intelligent local navigation. The path plan is obtained by using visibility graph and Dijkstra’s algorithm, and the local navigation uses fuzzy logic to control the robot's behavior. Experiments were done in two different sizes of mobile robots and the initial objectives were achieved. The results show that a shorter travelled distance were obtained, as well as on-time reaction to dynamic obstacles in the robot's path. The outcome is that the hybrid method provides a better solution than any of the methods alone, combining the efficiency of the path planning with the dynamic response of the local navigation technique.

碩士
國立臺灣科技大學
自動化及控制研究所
103
This study discusses the planning of a three-dimensional global optimization path for robots through the Ant Colony Optimization (ACO) and the Enhanced Ant Colony Optimization (EACO). In ACO, which was first proposed by Dorigo, the transition probability is composed of pheromone concentration and the length of two segments. This study intended to improve the deadlock caused by the cliffs, insufficient exploration rates, and slower convergence rates in the three-dimensional map, while the EACO targeted the correction of two parameters in transition probability: (a) Using the formula of the length of two segments, the weight of the altitude parameter was strengthened; (b) Using the pheromone concentration formula, the local pheromone updating mechanism was strengthened; (c) Using the determination formula, the ramp angle restrictions were added. A comparison of EACO and ACO shows that EACO has the advantages including faster convergence rates, shortening the path by up to 10%, and increasing the exploration rate by 10%. Evidence from computer simulation shows the EACO can accurately derive the best solution (i.e., the shortest global path) in the complex three-dimensional robot path planning environment.

碩士
國立成功大學
工程科學系碩博士班
98
Most mobile robots operate in a specific confined environment, such as schools, hospitals, offices, etc, with fixed moving paths and stationary objects. However, in such semi-static environments, dynamic interference, like moving people, moving objects, and changing surroundings, to their moving path may happen unexpectedly and result in obstructing the path of a robot. For robots to avoid dynamic obstructions and continue their journey, this study uses multiple ultrasonic sensors to collect real-time surrounding information and establishes a set of rules for detecting the heading and the speed of dynamic obstructions. The global and the local paths are then recalculated to lead robots to their destinations. The rules are realized as algorithms and are implemented to analyze information received from ultrasonic sensors, to trigger the recalculations of global and local paths, and to control the motors of wheels of a robot to avoid unexpected dynamic obstructions. Experiments have been conducted to verify the effectiveness of the mechanism used in this study, and they have yielded promising results.

碩士
國立臺灣科技大學
資訊工程系
96
In recent years, there have been more and more researchers taking interest in the development of autonomous mobile robots. These robots can help people in daily life, such as office robot, entertainment robot, and security robot. There are many issues; for example, perception of environments, localization, path planning, map building, and execution action, about the robot navigation in indoor environments. To move accurately and safely in an indoor environment is one of the important functionality of robot navigation. The aim of this thesis is to make the robot can know its location and the position of the obstacles surrounding it, and guide the robot to avoid the obstacles without collision. On our experimental robot, the stereo vision system plays an important role during the navigation, and the ultrasonic sensors system acts as an assistant to help the robot walking safely. We adopt stereo vision techniques to localize robot's location using the known landmarks when the robot navigates in an indoor environment. In obstacle detection, we combine the edge and color features to detect obstacles; in the experiments, we use the specific colored cones as obstacles. After obtaining the environmental information from stereo vision and ultrasonic sensors, the robot can plan the local path. The planed path can keep the robot moving safely and correctly. Then the robot will stop the navigation if it reaches the destination where we set the place as the goal. The experiments reveal that the relative error range of the global localization results is about 0°~10.4° for the orientation, 0~0.21 m for the lateral location, and 0.05~0.12 m for the depth location. These global localization results are sufficient to provide for the local path planning which can guide the robot to move safely and to keep it on the expected trajectory in an indoor environment.

A unique mathematical tool is developed to deal with global optimization of a set of engineering problems. These include image processing, mechanical topology optimization, and optimal path planning in a variational framework, as well as some benchmark problems in parameter optimization. The optimization tool in these applications is based on the level set theory by which an evolving contour converges toward the optimum solution. Depending upon the application, the objective function is defined, and then the level set theory is used for optimization. Level set theory, as a member of active contour methods, is an extension of the steepest descent method in conventional parameter optimization to the variational framework. It intrinsically suffers from trapping in local solutions, a common drawback of gradient based optimization methods. In this thesis, methods are developed to deal with this drawbacks of the level set approach. By investigating the current global optimization methods, one can conclude that these methods usually cannot be extended to the variational framework; or if they can, the computational costs become drastically expensive. To cope with this complexity, a global optimization algorithm is first developed in parameter space and compared with the existing methods. This method is called "Spiral Bacterial Foraging Optimization" (SBFO) method because it is inspired by the aggregation process of a particular bacterium called, Dictyostelium Discoideum. Regardless of the real phenomenon behind the SBFO, it leads to new ideas in developing global optimization methods. According to these ideas, an effective global optimization method should have i) a stochastic operator, and/or ii) a multi-agent structure. These two properties are very common in the existing global optimization methods. To improve the computational time and costs, the algorithm may include gradient-based approaches to increase the convergence speed. This property is particularly available in SBFO and it is the basis on which SBFO can be extended to variational framework. To mitigate the computational costs of the algorithm, use of the gradient based approaches can be helpful. Therefore, SBFO as a multi-agent stochastic gradient based structure can be extended to multi-agent stochastic level set method. In three steps, the variational set up is formulated: i) A single stochastic level set method, called "Active Contours with Stochastic Fronts" (ACSF), ii) Multi-agent stochastic level set method (MSLSM), and iii) Stochastic level set method without gradient such as E-ARC algorithm. For image processing applications, the first two steps have been implemented and show significant improvement in the results. As expected, a multi agent structure is more accurate in terms of ability to find the global solution but it is much more computationally expensive. According to the results, if one uses an initial level set with enough holes in its topology, a single stochastic level set method can achieve almost the same level of accuracy as a multi-agent structure can obtain. Therefore, for a topology optimization problem for which a high level of calculations (at each iteration a finite element model should be solved) is required, only ACSF with initial guess with multiple holes is implemented. In some applications, such as optimal path planning, objective functions are usually very complicated; finding a closed-form equation for the objective function and its gradient is therefore impossible or sometimes very computationally expensive. In these situations, the level set theory and its extensions cannot be directly employed. As a result, the Evolving Arc algorithm that is inspired by "Electric Arc" in nature, is proposed. The results show that it can be a good solution for either unconstrained or constrained problems. Finally, a rigorous convergence analysis for SBFO and ACSF is presented that is new amongst global optimization methods in both parameter and variational framework.

Background: Despite the contraceptive prevalence of 67.4% in Morocco, one woman out of 10 has unmet need for birth spacing or limiting and, only one woman out of two is using modern contraception. Although, Moroccan national family program [FP] was launched in the sixties and aimed to increase use of FP among married Moroccan women; the program is still facing some limits to improve couple’s contraceptive care. This paper examines to what extent women’s status, husband’s FP approval and mass media positive exposure to FP messages translate into increased modern contraceptive uptake. This study uses the socio ecological framework to assess factors that influence FP use among married women in Morocco. In this model factors from individual, interpersonal and programmatic levels were identified based on a review of the literature as having an effect on contraception use. Objectives: The main objectives of this study are to: (1) explore the effect of women’s status including their education, their occupation and, their FP decision making on women’s desire for more children, (2) examine if husbands’ FP approval impacts women’s fertility desire, (3) assess how positive mass media FP messages ‘exposure influences women’s desire for children, (4) explore the effect of women’s fertility desire on women’s FP approval and,(5) assess if women’s FP approval increases modern contraception adoption. Methods: This analysis is based on secondary data from the 2004 Demographic Health Survey and, 2011 Morocco National Survey on Population and Family Health which were conducted among married women aged between 15 and 49 years old. Data were collected using a two-stage sampling scheme and the study population was 8,106 women in 2004 and 9,317 women in 2011. Path analysis, using series of multiple regression modeling analyses, was conducted to investigate the relationship between women’s desire for more children and predictors related to women’s status, husbands’ FP approval and, women’s exposure to FP messages via mass media. Full models were fitted to test the relationships between women’s desire for more children and women’s FP approval; women’s approval of FP and modern contraception use. Results: Descriptive analysis between 2004 data and 2011 data analysis showed similar results for women’s and husbands’ predictors. Women in 2011 who used modern contraception were mostly aged more than 35 years old (51%), lived in urban areas (56%), mostly rich (40.3%), educated (46%), with no occupation (89%), did not decide FP use alone (73.3%), whose husbands discussed FP with them (62%) and, approved contraceptive use (98%). Positive exposures to FP messages on mass media were measured only in 2004 data and showed that among women who adopted modern contraception, only 2.9% read FP messages in newspapers, 12.6% heard them in the radio and 25.5% heard them on television. Path analyses showed some differences between 2004 data and 2011data. In 2011 data educated women were 1.42 (O.R. = 1.42, C.I. 1.26–1.6) more likely to desire more children than those with no education. Women with occupation were 1.25 (O.R. = 1.25, C.I. 1.01–1.47) times more likely to desire children than those with no occupation. However, women’s education and women’s occupation factors were not related to women’s fertility desire in 2004 data. Husbands’ FP approval was not significantly associated to women’s fertility desire in both 2004 and 2011 data analyses. Mass media exposure to FP messages was examined only in 2004 and showed no significant association with women’s fertility desire. Similar results were observed between 2004 data and 2011 data and showed that women who decided for FP were 0.75 (O.R. = 0.75, C.I. 1.01–1.47) times less likely to desire more children than those who were not FP decision makers. Moreover, in 2004 women who decided for FP were 2, 32 times more likely to use modern contraception than women who were not FP decision makers [O.R. 2, 31 (CI 1.79-3.01)]. In 2011 data analysis, women who approved FP were 5.72 (O.R. = 5.72, C.I. 3.06–10.7) more likely to use modern contraception than those who did not approve FP. Furthermore, women whose husbands approved FP were 2.55 times more likely to adopt modern contraception (O.R. = 2.55, CI 1.845-3.513). Conclusions: This study results indicated women’s and, husband’s factors affecting women’s fertility desire and women’s contraceptive use. The factors effects varied between 2004 data and 2011 data. In 2011 data women’s education, women’s occupation, women’s FP decision making and, husbands’ FP discussion variables, had a significant effect on women’s fertility desire. However, in 2004 data only husband’s FP discussion had a positive effect on women’s fertility desire which had a positive effect on women’s FP approval. Women’s exposure to mass media FP messages did not have a significant effect on both women’s fertility desire and women’s contraceptive outcomes. Husbands’ FP approval and husbands’ FP discussion with their wives were highly predictive for women’s contraceptive use and remained essential factors for which Moroccan health policy makers should take into consideration in order to reduce unmet needs and improve couple’s contraceptive care in Morocco.
acase@tulane.edu

abstract: Humans have modified land systems for centuries in pursuit of a wide range of social and ecological benefits. Recent decades have seen an increase in the magnitude and scale of land system modification (e.g., the Anthropocene) but also a growing recognition and interest in generating land systems that balance environmental and human well-being. This dissertation focused on three case studies operating at distinctive spatial scales in which broad socio-economic or political-institutional drivers affected land systems, with consequences for the environmental conditions of that system. Employing a land system architecture (LSA) framework and using landscape metrics to quantify landscape composition and configuration from satellite imagery, each case linked these drivers to changes in LSA and environmental outcomes. The first paper of this dissertation found that divergent design intentions lead to unique trajectories for LSA, the urban heat island effect, and bird community at two urban riparian sites in the Phoenix metropolitan area. The second paper examined institutional shifts that occurred during Cuba’s “special period in time of peace” and found that the resulting land tenure changes both modified and maintained the LSA of the country, changing cropland but preserving forest land. The third paper found that globalized forces may be contributing to the homogenizing urban form of large, populous cities in China, India, and the United States—especially for the ten largest cities in each country—with implications for surface urban heat island intensity. Expanding knowledge on social drivers of land system and environmental change provides insights on designing landscapes that optimize for a range of social and ecological trade-offs.
Dissertation/Thesis
Doctoral Dissertation Geography 2020