Abstract: A flexible two-wheeled self-balancing robot system and its motion control method include a main controller 1, a motion controller 2, an assistant controller 3, two servo drivers 4, sensors, input/output devices, two DC motors 5 and a power supply system; a camera is installed on truck's top board 11, a tilt-meter and a gyro are installed both in truck 6 and chassis 8. Truck 6 and chassis 8 are connected with an elastic joint in which is installed a two-arm torsion spring and a cylindrical spring; the main controller 1 is connected to the motion controller 2, the assistant controller 3 and input/output devices. The user commands received by the main controller 1 are immediate commands or stored commands; through main controller 1 running the motion behavior decision algorithm, the motion controller 2 running the motion balancing control algorithm, and the servo drives 4 controlling the torques of the motors 5, locomotion on plane and remote control of the robot can be implemented.

Abstract: A flexible two-wheeled self-balancing robot system and its motion control method include a main controller 1, a motion controller 2, an assistant controller 3, two servo drivers 4, sensors, input/output devices, two DC motors 5 and a power supply system; a camera is installed on truck's top board 11, a tilt-meter and a gyro are installed both in truck 6 and chassis 8. Truck 6 and chassis 8 are connected with an elastic joint in which is installed a two-arm torsion spring and a cylindrical spring; the main controller 1 is connected to the motion controller 2, the assistant controller 3 and input/output devices. The user commands received by the main controller 1 are immediate commands or stored commands; through main controller 1 running the motion behavior decision algorithm, the motion controller 2 running the motion balancing control algorithm, and the servo drives 4 controlling the torques of the motors 5, locomotion on plane and remote control of the robot can be implemented.

Abstract: A receiver having an adaptive maximum likelihood sequence (MLSE) estimator and method are provided, in particular in a nonlinear receiver, wherein a channel estimator is used to estimate the channel to be used in the MLSE estimator in order to minimize distortion. In the MLSE estimator, the channel estimation is extracted from the phase of the signal using a known training sequence pattern in the received data frame. The channel estimation is adaptively updated using a Least Mean Square (LMS) algorithm by applying tentative decision in the received signal.