Path Planning for Vehicles Operating in Uncertain 2D Environments
- 1st Edition - January 28, 2017
- Latest edition
- Author: Viacheslav Pshikhopov
- Language: English
Path Planning for Vehicles Operating in Uncertain 2D-environments presents a survey that includes several path planning methods developed using fuzzy logic, grapho-an… Read more
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Path Planning for Vehicles Operating in Uncertain 2D-environments presents a survey that includes several path planning methods developed using fuzzy logic, grapho-analytical search, neural networks, and neural-like structures, procedures of genetic search, and unstable motion modes.
- Presents a survey of accounting limitations imposed by vehicle dynamics
- Proposes modified and new original methods, including neural networking, grapho-analytical, and nature-inspired
- Gives tools for a novice researcher to select a method that would suit their needs or help to synthesize new hybrid methods
Scientists working in the area of system analysis, robotics and control systems; Vehicle control systems designers; Developers of control systems and algorithms for robotic complexes; post-graduate and graduate students studying robotics, control systems, mechatronics and preparing their theses
Chapter One. Position-Path Control of a Vehicle
- 1.1. Motion-Control Systems Problems Analysis
- 1.2. Mathematical Models of Motion
- 1.3. Motion Path Planning
- 1.4. Algorithms of Position-Path Control
- 1.5. Requirements of Path Planners
- 1.6. Summary
Chapter Two. Neural Networking Path Planning Based on Neural-Like Structures
- 2.1. Bionic Approach to Building a Neural Network–Based Vehicle Path Planner in 2D Space
- 2.2. Synthesis of Neural Networking Planner as a Part of Position-Path Control System. Task Statement
- 2.3. Development of the Basic Method of Determining the Vehicle's Motion Direction under the Conditions of Uncertainty
- 2.4. Bionic Method of Neural-Networking Path Search
- 2.5. Convolutional Neural Networks1
- 2.6. Summary
Chapter Three. Vehicles Fuzzy Control Under the Conditions of Uncertainty
- 3.1. Types of Uncertainties
- 3.2. Applications of Fuzzy Logic in Vehicles Control
- 3.3. Vehicle's Path Planning
- 3.4. Development of the Vehicle's Behavioral Model Using Fuzzy-Logic Apparatus
- 3.5. Vehicle Motion Control Principles
- 3.6. Summary
Chapter Four. Genetic Algorithms Path Planning
- 4.1. Generalized Planning Algorithm
- 4.2. Graph Formation
- 4.3. Development of Genetic Algorithms for Planning
- 4.4. Modeling Results of Using Genetic Algorithms for Path Finding
- 4.5. Imitation Modeling Results for Path Planning With Mapping
- 4.6. Summary
Chapter Five. Graphic-Analytical Approaches to Vehicle's Motion Planning
- 5.1. Potential-Field Method in Vehicles Control
- 5.2. Application of Voronoi Diagrams to Path Planning
- 5.3. Vehicle Motion Planning Accounting for the Vehicle's Inertia
- 5.4. Summary
Chapter Six. Motion Planning and Control Using Bionic Approaches Based on Unstable Modes
- 6.1. Non-Formalized Environments With Point Obstacles
- 6.2. Non-Formalized Environments With Complicated Obstacles
- 6.3. Coordinated Application of Unstable Modes and Virtual Point for Obstacle Avoidance
- 6.4. Summary
- Edition: 1
- Latest edition
- Published: February 1, 2017
- Language: English
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