Implementation and design of new low-cost foot pressure sensor module using piezoelectric sensor in T-FLoW humanoid robot

Basically, human can sense the active body force trough the soles of their feet and can feel the position vector of zero moment point (ZMP) based on the center of pressure (CoP) from active body force. This behavior is adapted by T-FLoW humanoid robot using unique sensor which is piezoelectric sensor. Piezoelectric sensor has a characteristic which is non-continuous reading (record a data only a moment). Because of it, this sensor cannot be used to stream data such as flex sensor, loadcell sensor, and torque sensor like previous research. Therefore, the piezoelectric sensor still can be used to measure the position vector of ZMP. The idea is using this sensor in a special condition which is during landing condition. By utilizing 6 unit of piezoelectric sensor with a certain placement, the position vector of ZMP (X-Y-axis) and pressure value in Z-axis from action body force can be found. The force resultant method is used to find the position vector of ZMP from each piezoelectric sensor. Based on those final conclusions in each experiment, the implementation of foot pressure sensor modul using piezoelectric sensor has a good result (94%) as shown in final conclusions in each experiment. The advantages of this new foot pressure sensor modul is low-cost design and similar result with another sensor. The disadvantages of this sensor are because of the main characteristic of piezoelectric sensor (non-continuous read) sometimes the calculation has outlayer data

Implementation and Integration of Fuzzy Algorithms for Descending Stair of KMEI Humanoid Robot

Locomotion of humanoid robot depends on the mechanical characteristic of the robot. Walking on descending stairs with integrated control systems for the humanoid robot is proposed. The analysis of trajectory for descending stairs is calculated by the constrains of step length stair using fuzzy algorithm. The established humanoid robot on dynamically balance on this matter of zero moment point has been pretended to be consisting of single support phase and double support phase. Walking transition from single support phase to double support phase is needed for a smooth transition cycle. To accomplish the problem, integrated motion and controller are divided into two conditions: motion working on offline planning and controller working online walking gait generation. To solve the defect during locomotion of the humanoid robot, it is directly controlled by the fuzzy logic controller. This paper verified the simulation and the experiment for descending stair of KMEI humanoid robot.&nbsp

Pengendalian Kecepatan Gerak Quadcopter Berbasis IMU pada Gerakan Tangan dengan Metode Template Matching

An aerial vehicle has actuator four brushless DC motors (quadcopter) which is operated using a remote control or automatically. An aerial vehicle commonly called a quadcopter is controlled by using sensor data Inertia Measurement Unit (IMU) especially gyroscope and accelerometer sensor. Motion control is a stick control with sensor data IMU as data input. The motion from the aerial vehicle is a two-dimension (2D) motion from X axis and Y axis. Data sensor IMU is read by a microcontroller and will be processed to get real data acceleration (acceleration without influenced gravitation) remotely. The distance gesture inertia and the speed at which it operates are the parameter that is converted into an air vehicle motion. Trajectory motion is changed into picture domain 10x10 pixel as the comparison with the template matching algorithm. Match motion recognition is a motion command to the quadcopter. The simple motion like vertical, horizontal, diagonal, and curve match 96% using template matching algorithm and trajectory estimation