ABSTRACT:
The real-time balance control of an eight link biped robot using a zero moment point (ZMP) dynamic model is difficult due to the processing time of the corresponding equations. To overcome this limitation, an intelligent computing control technique is used. This technique is based on support vector regression (SVR). The method uses the ZMP error and its variation as inputs, and the output is the correction of the robot’s torso necessary for its sagittal balance. The SVR is trained based on simulation data and their performance is verified with a real biped robot. The ZMP is calculated by reading four force sensors placed under each robot’s foot. The gait implemented in this biped is similar to a human gait that is acquired and adapted to the robot’s size. Some experiments are presented, and the results show that the implemented gait combined with the SVR controller can be used to control this biped robot. The SVR controller performs the control in 0.2 ms.
Existing System:
In earlier systems, wheeled vehicles robots are used. Wheeled vehicles have several limitations on rough and uneven surface. So in order to rectify this, we go for the new walking robot.
The Proposed System: The aim was to create walking robot which is more attractive than wheeled machines and its programming offers interesting problems to solve not only on the higher level of autonomous operation but also on the low level of microcontroller programming – which is useful for people who want to learn how to program microcontrollers and have some fun along the way. The building cost should be very low, and that’s why design with servos is used. In this work, we present the design and the implementation of an innovative walking robot. The mechanism consists of motors and gears, the motors were controlled through relays from microcontroller. The microcontroller gets command from PC through serial port. The walking robot is used in various applications in which wheeled robots cannot possible do the tasks.