本論文係探討大人形雙足機器人aiRobot-HBR1之運動控制系統設計，並利用感測器控制模組追蹤人體雙足姿態以控制機器人的動作與行為。aiRobot-HBR1是一個110公分、40公斤，具有12個自由度的大人形雙足機器人，文中描述機器人之運動控制系統架構與動作規劃方法，結合所設計的馬達控制器、人機介面與感測器控制模組，以Nios FPGA為處理核心，基於SOPC發展介面，構成一個發展機器人控制策略的平台。另外，本文建立感測器控制模組的動態模型，感測器控制模組融合了加速度計與陀螺儀，將感測器量測的資訊傳送至機器人的處理核心中，以卡爾曼濾波器估測動態模型的狀態，達成人體雙足姿態追蹤。結合機器人與人體雙足姿態追蹤，我們利用估測的雙足姿態控制雙足機器人，發展雙足機器人之即時人體雙足姿態追蹤控制與人體雙足姿態辨識方法。最後，由實際實驗結果來驗證所設計之運動控制系統效能，以及即時人體雙足姿態追蹤控制與人體雙足姿態辨識方法之效益。

This thesis presents the motion control system design of the human-sized biped robot, aiRobot-HBR1, and proposes a human biped motion (HBM) tracking control approach in which humans can control the robot by an integrated sensor control module (ISCM). aiRobot-HBR1 is a human-size biped robot with 110 cm height and 40 Kg weight, and has a total of 12 D.O.Fs.
First, this thesis presents the control structure of the motion control system and the motion pattern planning of the robot. Designing the motor controller, the graphic user interface, and the integrated sensor control module along with the central processor unit, Nios FPGA, we construct a control platform for developing the control strategies of the robot based on SOPC. Furthermore, this thesis establishes the dynamic model of the integrated sensor control module which integrates a gyro and an accelerometer. The Kalman filter is utilized to estimate the states of the model to track the human biped motion. Combining the biped robot with the tracking result of the human-body motion, we propose a real-time HBM tracking control and a HBM recognition approach. The estimated posture is used to control the motion and the behavior of aiRobot-HBR1. Finally, the experiment results indicate the validity of the proposed motion control system, real-time HBM tracking control, and the HBM recognition.

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