本論文提出一以嵌入式系統為核心所研發之具有自主路徑規劃與定位功能以及反應導航之全方位移動機器人控制系統。在機器人自主導航演算法上，本論文使用區域最佳快速拓展隨機樹（Local-optimized Rapidly-exploring Random Tree；LoRRT）以針對一未知環境規劃最佳導航路徑；並使用結合虛擬障礙物之人工位能場（Artificial Potential Field；APF）開發反應導航演算法；特別的是，本文加入虛擬障礙物於傳統APF演算法，使機器人避開導航死鎖點之情形。在系統實現上，本研究使用結合即時運動控制與系統決策之混合式核心（Hybrid-core）系統架構，其包括Intel XScale-PXA270之系統決策核心以及元件可程式邏輯閘陣列（Field Programmable Gate Array；FPGA）之運動控制核心。同時，FPGA 控制器使用可程式系統晶片（System on a Programmable Chip ； SoPC）技術實現軟硬體協同設計（Software/Hardware Co-design）之架構。在軟硬體元件配置上，本系統使用NIOS II 微處理器建構逆向運動學以及正向運動學數學模型，以使機器人達到即時運動之能力與定位之目的；並使用Verilog 建構通訊、馬達控制、馬達計數器以及超音波感測模組，以達即時訊號處理與介面擴充之目的。而PXA270 嵌入式系統則在嵌入式Linux作業系統上實現了LoRRT、APF、人機介面互動以及雷射環境地圖建構。最後，在實體機器人開發上，本研究以三輪全方位移動平台建構高機動性之移動平台
，並經由不同之測試條件來驗證此一系統在實際環境運作下之效能表現。

This thesis presents an embedded system based omni-wheeled robot control system to deal with autonomous path planning, odometry localization and reactive navigations. A Local-optimized rapidly-exploring random tree (LoRRT) is proposed to plan feasible navigation paths for unknown environments. At the same time, an artificial potential field (APF) approach is used by combining virtual obstacles to perform reactive navigations. Especially, the novel virtual obstacle approach effectively resolves the deadlock or oscillation situations when compared to conventional APF approaches. The proposed control system is implemented in terms of a hybrid-core system architecture which combines an Intel XScale-PXA270 based decision kernel and a field programmable gate array (FPGA) based motion control kernel. The FPGA controller is further developed using the system on a programmable chip (SoPC) technique to realize software/ hardware co-design architecture. The software module is implemented upon a NIOS II microprocessor, which is used to carry out the algorithms for kinematics based robotic odometry and motion controls. The verilog hardware modules are constructed to deal with serial communications, motor counters, motor controls and ultrasonic sensor collections so that the real-time signal processing and frequent I/O interrupts can be well arranged. On the other hand, the XScale-PXA270 embedded system is responsible of the algorithm implementations for LoRRT, APF, human-machine interface and laser range finder based map construction based on an embedded Linux operation system. Finally, a three omni-wheeled robot platform is fabricated in our laboratory. Several practical experiment results are discussed based on ground-truth evaluations to verify the performance of the proposed control system.

[1] S.Y. Chung and H.P. Huang, “Relative-Absolute Information for Simultaneous Localization and Mapping,” IEEE International Conference on Robotics and Biomimetics, pp. 1641 - 1646, 2007.
[2] Y. Cen, L. Wang and H. Zhang, “Real-time Obstacle Avoidance Strategy for Mobile Robot Based On Improved Coordinating Potential Field with Genetic Algorithm,” IEEE International Conference on Control Applications, pp. 415-419, 2007.
[3] J. Gonzalez, C. Galindo, J.L. Blanco, J.A. Fernandez-Madrigal, V. Arevalo and F.A. Moreno, “SANCHO, a Fair HostRobot. A Description,” IEEE International Conference on Mechatronics, pp. 1-6, 2009.
[4] S. Khanmohammadi and A. Mahdizadeh, “Density Avoided Sampling: An Intelligent Sampling Technique for Rapidly-Exploring Random Trees,” International Conference on Hybrid Intelligent Systems, pp. 672-677, 2008.
[5] Y. Koren and J. Borenstein, “Potential Field Methods and their Inherent Limitations for Mobile Robot Navigation,” IEEE International Conference on Robotics and Automation, Vol. 2, pp. 1398-1404, 1991
[6] O. Khatib, “Real-Time Obstacle Avoidance for Manipulators and Mobile Robots,” IEEE International Conference on Robotics and Automation, pp. 500-505, 1985.
[7] S.M. LaValle, “Rapidly-Exploring Random Trees: A New Tool for Path Planning,” TR98-11, Computer Science Dept, Iowa State University, 1998.
[8] C. Liu, J. Chang, G. Li and C. Liu, “Mobile Robot Path Planning based on an Improved Rapidly-Exploring Random Tree in Unknown Environment,” IEEE International Conference on Automation and Logistics, pp. 2375-2379, 2008.
[9] K.H. Lin, H.S. Lee and W.T. Chen,“Implementation of Obstacle Avoidance and ZigBee Control Functions for Omni Directional Mobile Robot,” IEEE Workshop on Advanced robotics and Its Social Impacts, pp. 1-5, 2008.
[10] H. Mano, K. Kon, N. Sato, M. Ito, H. Mizumoto, K. Goto, R. Chatterjee and F. Matsuno, “Treaded Control System for Rescue Robots in Indoor Environment,” IEEE International Conference on Robotics and Biomimetics , pp. 1836-1843, 2009
[11] M.N. Mahyuddin, C.Z. Wei and M.R. Arshad, “Neuro-fuzzy Algorithm Implemented in Altera's FPGA for Mobile Robot's Obstacle Avoidance mission,” IEEE Conference on TENCON, pp. 1-6, 2009.
[12] J. Nieto, E. Slawinski, V. Mut and B. Wagner, “Online Path Planning based on Rapidly-Exploring Random Trees,” IEEE International Conference on Industrial Technology (ICIT), pp. 1451-1456, 2010.
[13] A.G. Ozkil, S. Dawids, Z. Fan and T. Srensen, “Design of a Robotic Automation System for Transportation of Goods in Hospitals,” International Symposium on Computational Intelligence in Robotics and Automation, pp. 392-397, 2007.
[14] E. Szadeczky-Kardoss and B. Kiss, “Extension of the Rapidly Exploring Random Tree Algorithm with Key Configuration for Nonholonomic Motion Planning,” IEEE International Conference on Mechatronics, pp. 363-368, 2006.
[15] H. Shi, C. Sun, X. Sun and T. Feng, “Chaotic Potential Field Method and Application in Robot Soccer Game,” World Congress on Intelligent Control and Automation, Vol. 2, pp. 9297-9301, 2006.
[16] Z. Su, B. Zeng, G. Liu, F. Ye and M. Xu, “Application of Fuzzy Neural Network in Parameter Optimization of Mobile Robot Path Planning Using Potential Field,” IEEE International Symposium on Industrial Electronics, pp. 2125-2128, 2007.
[17] Y. Tian, L. Yan, G. Park, S. Yang, Y. Kim, S. Lee and C. Lee, “Application of RRT-based Local Path Planning Algorithm in Unknown Environment,” International Symposium on Computational Intelligence in Robotics and Automation, pp. 456-460, 2007.
[18] C.C. Tsai, S.M. Hsieh, Y.P. Hsu and Y.S. Wang, “Human-robot Interaction of an Active Mobile Robotic Assistant in Intelligent Space Environments,” IEEE International Conference on Systems, Man and Cybernetics, pp. 1953-1958, 2009.
[19] Y. Wang, J. Wang and S. Yin, “An Object-Based Path Planning Using Grids-Potential Fields for Intelligent Robot,” International Conference on Genetic and Evolutionary Computing, pp. 150-153, 2009.
[20] D.F. Wolf, J.A. Holanda, V. Bonato, R. Peron and E. Marques, “An FPGA-Based Mobile Robot Controller,” IEEE Southern Conference on Programmable Logic, pp. 119-124, 2007.
[21] J. Xiao, A. Calle, J. Ye and Z. Zhu, “A Mobile Robot Platform with DSP-based Controller and Omnidirectional Vision System,” IEEE International Conference on Robotics and Biomimetics, pp. 844-848, 2004.
[22] H. C. Yen, H. P. Huang and S.Y. Chung, “Goal-directed Pedestrian Model for Long-term Motion Prediction with Application to Robot Motion Planning,” IEEE Workshop on Advanced robotics and Its Social Impacts, pp. 1-6, 2008
[23] K. Yang and S. Sukkarieh, “Real-time Continuous Curvature Path Planning of UAVS in Cluttered Environments,” International Symposium on Mechatronics and Its Applications, pp. 1-6, 2008.
[24] Y. Zhu, T. Zhang and J. Song, “An Improved Wall Following Method for Escaping from Local Minimum in Artificial Potential Field based Path Planning,” IEEE Conference on Decision and Control, pp. 6017-6022, 2009.
[25] B. Zhang, W. Chen and M. Fei, “An Optimized Method for Path Planning Based on Artificial Potential Field,” International Conference on Intelligent Systems Design and Applications, pp. 35-39, 2006.
[26] Q. Zhu, Y. Yan and Z. Xing, “Robot Path Planning Based on Artificial Potential Field Approach with Simulated Annealing,” International Conference on Intelligent Systems Design and Applications, Vol. 2, pp. 622-627, 2006.
[27] 毛曉宇，「醫院服務型機器人開發」，碩士論文，長庚大學，民國97年。
[28] 蔡勝宇，「FPGA之自主式吸塵器導航控制器開發」，碩士論文，長庚大學，民國98年。
[29] 王進德，嵌入式Linux程式設計修訂版，全華科技圖書股份有限公司，2006。
[30] 江俊龍（譯），Linux程式設計教學手冊（第三版），碁峯資訊股份有限公司，2004。
[31] 黃英叡、黃稚存，Verilog 硬體描述語言（第二版），全華科技圖書股份有限公司，2005。
[32] 飆機器人網站，http://www.playrobot.com/home_index.htm
[33] PXA270介紹，http://www.microtime.com.tw/
[34] Motion Capture介紹，http://www.pitotech.com.tw/
[35] RRT演算法介紹，http://msl.cs.uiuc.edu/rrt/index.html
[36] RRT演算法介紹，http://www.kuffner.org/james/plan/algorithm.php
[37] RRT演算法介紹，http://en.wikipedia.org/wiki/Rapidly-exploring_random_tree
[38] RRT演算法介紹，http://www.techunited.nl/wiki/index.php/Path_planning:_RRT_-_Introduction
[39] 雷射測距儀介紹，http://www.hokuyo-aut.jp/02sensor/07scanner/download/index.html
[40] 東方馬達介紹，http://www.orientalmotor.com.tw/
[41] FPGA介紹，http://www.altera.com/
[42] Verilog程式介紹，http://www.fpga4fun.com/index.html