학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 2. 이범희. ; In order to autonomously navigate in an unknown environment, a mobile robot should perceive the environments precisely and generate fast-moving path without collisions. In recent years, as the operating environment is becoming more and more complicated, considering various factors such as multiple agents, moving obstacles becomes an important issue in autonomous navigation. Therefore, it is necessary to develop a collision avoidance navigation algorithm which is effective in a variety of situations. A centralized navigation system collects information of the environments and all robots, and decides trajectories of each robot. As the environment gets more complex, calculating the collision-free trajectory is difficult. A distributed navigation system which controls the robot individually cannot guarantee optimal path of the robot, but it is easy to apply depending on the situation. This dissertation addresses local and reactive navigation without centralized coordination or control. A velocity obstacle approach one of local and reactive navigation methods is re-analyzed here. Most of the conventional velocity obstacle approaches are analyzed in Cartesian coordinates. The proposed approach of this dissertation performs collision prediction and avoidance motion planning of a mobile robot with non-linear velocity based on robot-centered polar coordinates. By re-analyzing the velocity obstacles concept in robot-centered polar coordinates, obstacle avoidance process has been simplified. Depending on the direction of the robot and the moving obstacles, the robot occasionally selects oscillating velocity as a result of using the conventional velocity obstacle approaches. In order to overcome the oscillation, new strategy which decides velocity of the robot to avoid collision with the oscillation-free path is designed. The proposed evaluation function is containing the current status of the robot, the relation between the robot and the obstacle, and the distance to the destination. The evaluation function is used for the robot velocity decision. Numerous simulations have been implemented to validate the proposed approach as well as the conventional algorithms. The performance of the proposed approach is verified by comparing the traveling time, distance, and computation time, and the smoothness of the robot path with the conventional algorithms. ; Chapter 1 Introduction 1 1.1 Background and motivation 1 1.2 Related works 4 1.3 Contribution 9 1.4 Organization 13 Chapter 2 Velocity Obstacle Approaches 14 2.1 Velocity Obstacles 14 2.2 Dynamic Velocity Space 17 Chapter 3 Problem Description of Reactive Control 23 3.1 Reactive Control in Cartesian and Polar Coordinates 23 3.2 Basic Assumptions and Definitions 28 Chapter 4 Velocity Obstacles in Polar Coordinates 32 4.1 Robot-centered Polar Coordinate Representation of an Obstacle 32 4.2 Desired Velocity Generation 34 4.3 Velocity Obstacle Region Generation 36 4.4 New Velocity Decision 42 4.4.1 Basic Method of Choosing Alternative Velocity 42 4.4.2 Proposed Method: Evaluating Two Alternatives 45 4.5 Kinematic Constraints and Execution 49 Chapter 5 Analysis of Velocity Obstacles in Polar Coordinates 52 5.1 Collision-free Navigation 52 5.2 Smoothness of the Robot Trajectory 60 5.3 Local Minima Avoidance 64 Chapter 6 Simulation Results 73 6.1 Implementation Setups 73 6.2 Simulations with a Single Dynamic Obstacle 75 6.2.1 Scenario 1: An Obstacle with Zero Angular Velocity 76 6.2.2 Scenario 2: An Obstacle with Non-Zero Angular Velocity 83 6.3 Simulations with Multiple Dynamic Obstacles 86 6.3.1 Scenario 3: Four Moving Obstacles 89 6.3.2 Scenario 4: Ten Moving Obstacles 94 6.3.3 Scenario 5: Seven Moving Obstacles in a Circle 99 6.3.4 Scenario 6: Five Moving Obstacles with Velocity Changes 102 Chapter 7 Conclusions 106 ; Doctor


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    Titel :

    Reactive Collision Avoidance Using the Velocity Obstacles Concept in Polar Coordinates



    Erscheinungsdatum :

    2014-01-01


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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