| Summary: | 碩士 === 國立中央大學 === 電機工程學系 === 105 === This thesis applies a fuzzy neural network controller and Kalman filter to control the hexapod for wall following and efficiently adjust the gait to realize stability locomotion. According to the angle position, measured by ultrasonic sensor, between the robot and the wall, the fuzzy neural network controller can control the swing amplitude of the left and right legs of the robot, so that the robot can walk in the complex environment successfully. In addition to walking in an unknown environment, the stability of the hexapod is also a very important theme. The Kalman filter uses an accelerometer and a gyroscope to obtain the real-time robot body attitude, while the tilt angles are separated to the leg directions to change the amplitude by inverse kinematics. Thus, the robot can move forward, and instantly restore horizontal body attitude when walking on oblique terrain. The experimental results show that the method proposed in this research can successfully applied to a real hexapod robot control.
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