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系統識別號 U0026-2308201701573800
論文名稱(中文) 在動態環境下非凸地圖之障礙物回避
論文名稱(英文) Obstacle avoidance for non-convex map and dynamic environment
校院名稱 成功大學
系所名稱(中) 航空太空工程學系
系所名稱(英) Department of Aeronautics & Astronautics
學年度 105
學期 2
出版年 106
研究生(中文) 周威廷
研究生(英文) Wei-Ting Chou
學號 P46041306
學位類別 碩士
語文別 英文
論文頁數 67頁
口試委員 指導教授-王大中
口試委員-詹劭勳
口試委員-彭兆仲
中文關鍵字 危險區域  動態物體避障  路徑規劃 
英文關鍵字 Danger Zone  obstacle avoidance  path planning 
學科別分類
中文摘要 近年來,自動駕駛的議題受到高度的關注,一台車子要可以達到完全的自動駕駛需要包含:自身定位、導航、路徑規劃、障礙物偵測與避障。本研究重點著眼於路徑規劃與複雜的未知環境避障,並使用U-字型障礙物作為非凸地圖之範例。在模擬環境中,使用單一感測器來測障礙物並得到自身位置與靜態障礙物的相對關係,引入Danger Zone的概念,即透過自走車與障礙物的相對速度,建立碰撞曲線,在以此概念發展動態物體即時閃避功能。最後利用Simultaneous Localization And Mapping (SLAM)演算法建立地圖,進而達成兼具探索與閃避移動障礙物之功能。
英文摘要 Autopilot technology is not yet fully mature. An autopilot vehicle requires self-localization, navigation, path planning, obstacle detection and obstacle avoidance. Path planning and obstacle avoidance in complex unknown environments are the focus of in this research, with a use U-shaped obstacle as an example of a non-convex map. In the simulation environment, single sensor is used to detect obstacles and get the relationship between the positions of the autonomous car and obstacles. In path planning and obstacle avoidance, we introduce the concept of a danger zone. which builds a collision curve based on the relative velocity between the autonomous car and obstacles. We also develop an avoidance function for dynamic obstacles, and then use the Simultaneous Localization And Mapping(SLAM) algorithm to build maps so that the autonomous car can explore these and avoid moving objects.
論文目次 摘要 I
ABSTRACT II
致謝 III
TABLE OF CONTENTS IV
LIST OF FIGURES VI
LIST OF TABLES IX
NOMENCLATURE X
CHAPTER 1 INTRODUCTION 1
1.1 Motivation 1
1.2 Literature Review 3
1.3 Outline of This Research 7
CHAPTER 2 OBSTACLE AVOIDANCE METHOD 8
2.1 Previous Path Planning Algorithm 8
2.2 The Basic Concept of the Danger Zone 11
2.3 Derivation and Analysis of the Danger Zone 13
2.4 Calculation of the Danger Zone with Linear Inequality Constraints 16
2.5 Representation of the Danger Zone with Quadratic Inequality Constraints 19
2.6 R-composition 24
2.7 Objective Function 25
CHAPTER 3 EXCEPTION HANDLING OF DANGER ZONE ALGORITHM 27
3.1 U-shaped Obstacle 27
3.2 New Objective Function and Adding Constraint 29
3.3 Concept of Exception Handling 31
3.4 Dynamic Weighting 33
CHAPTER 4 SIMULATION OF THE SYSTEM 43
4.1 Experiment Hardware 44
4.2 Experiment Setup 45
4.2.1 Choosing the Operating System Platform and Software 45
4.2.2 Building a Car Model 47
4.2.3 Speed Control 49
4.3 Discussion and Result 53
CHAPTER 5 CONCLUSION AND FUTURE WORK 64
REFERENCES 65
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