本研究實現小型(Kidsize)人型機器人在環境中的同時自我定位與建立地圖功能。首先,設計與製作符合RoboCup規格的人型機器人;其次,探討人型機器人正反向運動學,進而規劃機器人的行走步態。最後,使用卡爾曼濾波器實現機器人同時自我定位與建圖功能。藉由電腦模擬與實驗完成同時自我定位與建圖演算法。實驗結果證明機器人在足球場上可以依賴已知位置的標示物達到自我定位。
In this thesis, a simultaneous localization and mapping (SLAM) algorithm is developed for a RoboCup Kidsize humanoid robot. This research is divided into three stages. First, we design and fabricate a humanoid robot which is conformed to the regulation of RoboCup Kidsize humanoid robot league. Second, forward and inverse kinematics for the designed humanoid robot is investigated. Based on the kinematics analysis, several walking patterns are also planned for the robot. Finally, we utilize Kalman filter to implement SLAM on this humanoid robot system. Both of the computer simulation and experimental work are performed to verify the proposed SLAM algorithm. The results show that the humanoid robot system can locate its position on a planar soccer field according to the position of a beacon.