透過您的圖書館登入
IP:18.116.28.246
  • 學位論文

基於紅外線感測器與超音波感測器之跟隨機器人設計

Infrared -Sensor and Ultrasonic-Sensor Based Following Robot Design

指導教授 : 吳俊德
若您是本文的作者,可授權文章由華藝線上圖書館中協助推廣。

摘要


近年來,機器人的發展越來越快速,種類也是五花八門,我們以自動跟隨的機器人為本論文的研究主題,本文介紹了一種方法用於自動跟隨的機器人系統。 首先,此機器人系統透過實驗平台中,紅外線感測器的發射與接收,來判讀以及比較差異,進而決定機器人移動的方向。其中我們使用了編碼器,將波型經由編碼以及計算,得其平台移動速度,選擇最佳執行模式,進行相應的動作來控制電機的旋轉。另外,由於紅外線感測器的位置距離會影響其精準度。 因此我們也嘗試了許多紅外線感測器在實際環境中運作的差異,並且記錄了各種不同模組所產生的結果以及優缺點,提供了仿真和實驗結果,以支持結論。

並列摘要


Nowadays, the service-oriented robot industries have been the focus of the national development. e.g., cleaning robot, intelligent robot, mobile robot, etc. This paper focuses on mobile robots. Generally, human-following robots are mostly based on image recognition, but image recognition still has many unsolved problems. In the market products, image recognition mostly uses acceptance mistake system because recognition results cannot achieve one hundred percent accuracy so it cannot be applied to precision control machine. This thesis proposed a method to solve this problem. To use six ultrasonic sensors and eight infrared sensors. Ultrasonic sensors sense the values, and then compare the difference with each other sensors in order to decide which direction the mobile robot will move. When the robot is running the infrared sensors can detect obstacles, and the robot will avoid it. The experimental results proved the robot can effectively complete the task with five kilograms load and an emergent switch. In the future, these mobile robots can apply supervision-system, which will help our life easier and better.

參考文獻


[1] Hannes Bergkvist,”Quadcopter Control using Android-based Sensing”,Lund university, Department of Automatic Control,2013
[2] J. H. Connell, Minimalist Mobile Robotics. Boston: Academic, 1990.
[3] K. Qian, X. Ma, X. Dai, and C. Hu, “A multi-camera approach to tracking and localization of people with coexisting robots,” IEEE 7th World Congress on Intelligent Control and Automation, pp. 5162-5167, 2008.
[4] C.H. Huang, W.J. Wang, and C.H. Chiu, “Design and implementation of fuzzy control on a two-wheel inverted pendulum,” IEEE Trans. Ind. Electron., vol. 58, pp. 2988-3001, 2011.
[5] C. Qiu and Y. Huang, “The design of fuzzy adaptive PID controller of two-wheeled self-balancing robot,” International Journal of Information and Electronics Engineering, vol. 5, pp. 193-197, 2015.

延伸閱讀