本論文以FPGA（Field Programmable Gate Array）軟硬體協同設計方式實現大型人形機器人步態控制器。此一方法相較於一般使用DSP（Digital Signal Processors）、單晶片微控器之純軟體設計方式，軟硬體協同設計可針對系統程序之特性，彈性地規劃軟體程式與硬體模組，有效地達成應用目標。在軟體設計部分，本文以 NIOS II可程式化晶片系統（System on a Programmable Chip）開發人形機器人步態產生器，其主要負責人形機器人線性倒單擺模型（Linear Inverted Pendulum Model）質心軌跡規劃、擺線方法之擺盪腳軌跡規劃以及逆向運動學計算；而硬體設計部分，則以Verilog開發1Mbps高速串列通訊介面來控制人形機器人之關節伺服馬達，以提高系統執行效率。為了驗證此一人形機器人步態控制器之可行性，本文以FIRA HuroCup大型人形機器人之馬拉松比賽進行相關實驗。其以PC環境來開發影像辨識系統，辨識機器人與地上線段之距離和方向差異來進行步態參數決策，並透過串列介面將步態參數傳送到FPGA人形機器人步態控制器，達到人形機器人自主循跡行走之目的。

This study presents a field programmable gate array (FPGA) based hardware/software co-design approach to implement a biped locomotion controller for an adult-size humanoid robot. The proposed hardware/software co-design approach is capable of flexibly arranging hardware and software components and modules in systems according to their characteristics to achieve specific application purposes when compared to dedicated microcontroller based solutions. For the software components, this study uses the NIOS II-based system on a programmable chip (SoPC) technique to generate joint angles with respect to reachable parametric locomotion commands. The software components developed in this work are composed of linear inverted pendulum model (LIPM) based center of mass (CoM) trajectory planning, cycloid trajectory planning for the swing foot and inverse kinematics. The main hardware module in this system is a 1 Mbps high speed serial communication module, and it is used to control the smart servo motors used for actuating joint movements of a humanoid robot. To validate the feasibility the proposed FPGA-based biped locomotion controller, this study employs the FIRA HuroCup marathon game as a test environment. The vision system is implemented with a PC-based system. The image processing and recognition approaches are responsible for recognizing the distance and heading angle to the line segment appeared in front of the robot. The distance and heading angle to the line segment information is further used to determine parametric locomotion commands. Finally, the generated parametric locomotion command is transmitted to the FPGA-based biped locomotion controller to control the robot to autonomously follow a specific marathon track.

[1]A. Yin and Y. Xing, “Operators to dilate and erode color impulse noise,” International Conference on E -Business and E -Government (ICEE), pp. 1-3, 2011.
[2]C.Y. Lin and Y.P. Chiu, “The DSP based catcher robot system with stereo vision,” IEEE International Symposium on Advanced Intelligent Mechatronics, pp. 897-903, 2008.
[3]E. Calvo-Gallego, A.C. Aldaya, P. Brox, and S. Sanchez-Solano, “Real-time FPGA connected component labeling system,” 19th IEEE International Conference on Electronics, Circuits and Systems (ICECS), pp. 593-596, 2012.
[4]F. Zhang, S.Y. Zhou, and W.L. Xie, “A line labeling and region growing based algorithm for binary image connected component labeling,” Second Pacific-Asia Conference on Circuits,Communications and System (PACCS), pp. 487-490, 2010.
[5]G. Hao, L. Min, and H. Feng, “Improved self-adaptive edge detection method based on Canny,” International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), pp. 527-530, 2013.
[6]H. Zhao, G.F. Qin, and X.J. Wang, “Improvement of canny algorithm based on pavement edge detection,” 3rd International Congress on Image and Signal Processing (CISP), pp. 964-967, 2010.
[7]J. Canny, “A computational approach to edge detection,” IEEE Transaction. Pattern Analysis and Machine Intelligence, pp. 679-714, 1986.
[8]L. He, Y. Chao, K. Suzuki, and K. Wu, “Fast connected-component labeling,” Pattern Recognition, vol. 42, no. 9, pp. 1977-1987, 2009.
[9]L. He, Y. Chao, and K. Suzuki, “A Run-based two-scan labeling algorithm,” IEEE International Symposium on Image Processing, pp. 749-756, 2008.
[10]L.F. He, X. Zhao, Y. Yang, H.P. Tang, and Y.Y. Chao, “Fast connected-component labeling for binary hexagonal images,” IEEE Region 10 Conference (31194) , pp. 1-4, 2013.
[11]M.P. Deisenroth and H. Ohlsson, “A general perspective on Gaussian filtering and smoothing explaining current and deriving new algorithms,” American Control Conference (ACC), pp. 1807-1812, 2011.
[12]M. Frenando and J. Wijayanayaka, “Low cost approach for real time sign language recognition,” IEEE International Conference on Industrial and Information Systems (ICIIS), pp. 637-642, 2013.
[13]M.K. Moghimi and H. Pourghassem, “Shadow detection based on combinations of HSV color space and orthogonal transformation in surveillance videos,” Iranian Conference on Intelligent Systems (ICIS), pp. 1-6, 2014.
[14]W.K. Lee and S. Jung, “FPGA design for controlling humanoid robot arms by exoskeleton motion capture system,” IEEE International Conference on Robotics and Biomimetics, pp. 1378-1383, 2006.
[15]吳志祥，「應用全方位移動機器人搜尋音源方位」，碩士論文，國立成功大學，民國96年。
[16]林奕巡，「以系統晶片實現機械臂影像運動控制」，碩士論文，國立台灣科技大學，民國102年。
[17]邱仕榮，「移動平台與手臂運動控制器之設計與實現」，碩士論文，國立成功大學，民國98年。
[18]許宥仁，「全自主電動載具導航與控制之感測器融合系統之開發」，碩士論文，國立成功大學，民國99年。
[19]連育德，「以平滑支撐向量迴歸為基礎之大型雙足機器人類人倒單擺軌跡規劃」，碩士論文，國立台灣科技大學，民國102年。
[20]黃明寶，「小型人形機器人之步態規劃與實作」，碩士論文，國立成功大學，民國100年。
[21]戚守為，「考慮陰影干擾之自主人形機器人於Robocup足球賽避障導航控制」，碩士論文，國立台灣科技大學，民國102年。
[22]張峻銘，「人形機器人足球賽視覺與策略系統之設計與實現」，碩士論文，國立成功大學，民國98年。
[23]楊俊卿，「二足步行機器人運動控制晶片之研製」，碩士論文，南台科技大學，民國98年。
[24]蔡偉成，「應用灰階影像形態學於六角影像上之邊緣偵測」，碩士論文，國立中山大學，民國101年。
[25]蕭佑緯，「全向輪移動式雙臂機器人之整體動態行為控制」，碩士論文，國立台灣科技大學，民國102年。
[26]鍾睿洲，「具重心高度調適之雙足線性倒單擺步行控制」，碩士論文，國立台灣科技大學，民國101年。