The demand for faster computation speed in modern digital signal processing is huge. However, the computation speed that single processor can provide is limited. To address this demand, both distributed system and parallel processing are becoming a requirement in an embedded system. Therefore, research about algorithm and application of parallel processing is very important to be conducted. Implementing MPI's standard to an embedded system will increase the application portability, therefore parallel programming will be easier to be implemented. This paper presents a novel design and implementation of MPI on top of our microkernel named FLoW which are built and run on an embedded system. To decrease communication latency, we propose a communication layer design based on MPI. On this layer, a process manager is made to handle multi-processes and routing services mechanism. In addition, a mailbox system is created to temporarily keep the message which is sent when the collective operation occurs. From our experiments, the time required to complete the data transmission process ranges from 400 to 500 microseconds for each process, and in parallel task testing using MPI, the speedup can achieve up to 40-50%.

The use of 3D Professional Camera to create a 3D video is still rarely used due to the high price of the camera. Mostly, people produce 3D movies using two 2D cameras which are set precisely the same by arranging the camera one by one. Using the 3D camera makes the setting is much easier. The 3D Professional Camera provides convenience with the two lenses that have been connected so that the camera settings also become one. However, the technique of making movies using 3D Professional Camera needs to be studied furthermore. This paper presents the experiments to gain the optimum setting for 3D Professional Camera in making a short movie. The configuration will result the 3D effects on the movie.

The real-time operating system (RTOS) is a software that contains the resources of a hardware device, and provides the facility to run the application in real-time by doing the task according to the given deadline. FLoWRTOS is a RTOS running on an embedded system device, which is being built by the EEPIS Robotics Research Center (ER2C) on the ARM Cortex-M4 platform of the i.MX6SoloX processor. In contrast to the real-time operating system in general, FLoWRTOS performs task scheduling based on deadline priority, this allows performance of FLoWRTOS to be optimized in the absence of an idle time of all the scheduled tasks. Tests were conducted to evaluate the performance of FLoWRTOS, and also on the implementation of FLoWRTOS on a plant, which is the head system of T-FLoW robot. The result shows that FLoWRTOS can run many tasks with a condition that the CPU utilization is less than equal to 0.8. And if the CPU utilization approaches less than equal to 1, at a certain time it will cause the task to run past the deadline because FLoWRTOS is still non-preemptive.

This work proposes how to build knowledge for 3D Modeling Gesture Javanese Dance. Trajectory build from precision movement from the original (real) dancer. By using basic motion 3D primitive and survey data, the degree of freedom (DOF) movement and roll-pitch-yaw rotations, could be detected. After, to get the motion gesture from motion capture, we create lots of joints which have complexity as a human dance. At the end, the purpose why we create skeletons for hands and legs also get the data gestures, is to calculate the difference percentage (error) from the gestures basic motion 3D primitive by survey data and by motion capture.

This paper presents a trash detection and classification system that will be implemented on a social-education trash bin robot. The robot is expected can be implemented in public facilities, like airport, railway station, hall and more which is there are a lot of people that potentially producing waste. We use Haar-Cascade method to first detect any objects on the floor. Then, Gray-Level Co-Occurrence Matrix (GLCM) and Histogram of Oriented Gradient (HOG) are combined to get a set of features. Support Vector Machines (SVM) is used to classify the features into organic waste, non-organic waste, and non-waste. Offline testing of classification system using 5-fold Cross Validation method obtain 82,7% of accuracy. Online testing of detection and classification system obtain 63.5% of accuracy with the best distance gained when the camera is tilted down to -40° with minimum distance for detection is 80 cm and 200 cm for maximum detection. By using this robot, it is expected to help instill the habit of disposing of garbage in the right place. The purpose of this research is making people aware of handling their waste in the right way and hopefully, it can reduce the waste problem.

This paper presents an early warning and reporting system to support mobile trash bin robot operations when collecting trashes. To support its task, we equipped it with an ability to estimate working time of the robot by considering robot's power supply and the trash level. To estimate the availability of robot's working time, we utilize the power supply voltage data that is smoothed using Kalman Filter to reduce noises. The output of the working time estimation system and trash level are then fed to the decision-making system. The warning will be reported to the cleaning service operator when a specific condition occurs. To do that, our robot is also equipped with an ability to communicate with the operator over internet which is specifically developed by us using TelegramBot. Operator can request data from the robot as needed, such as battery information, trash level, estimated working time from the battery, and operator can also turn off the robot's work. Our experiments using 4G LTE Network has an average latency of 11.94011 seconds and using WiFi network has an average latency of 6.066273 seconds.

The main parameters to generate and calculate dynamics system models is position of each joint from its origin position. This paper describes about full body calculation position of each joint based on system design of "T-FLoW" humanoid robot using forward kinematics (FK) analysis. The FK analysis is used to transform the rotational value (degree) of each joint into position vector (cartesian space) of each joint. FK analysis in each joint is combined step by step from its origin until reach the last joint number (end of effector - EoE). The result from this combination is position vector of each joint from its origin. From the result shows the full body FK analysis with homogenous transformation method is represent the real pose of T-FLoW humanoid robot. This full body joint position vector is used to complete the dynamics system model calculation of T-FLoW humanoid robot.

T-FLoW (Teen FLoW) is one of the teen size humanoid robots developed by ER2C (EEPIS Robotics Research Center) laboratory. There are various problems that occur when the robot performs dynamic locomotion, one of them is the overloading received on every actuator thus causing the asynchronous locomotion of the robot. In this paper, the goal to be achieved is making a vertical jumping mechanism of the robot to become more synchronized. Therefore, multivariable control will be used as a method to distribute overload for each actuator on the same joint so that actuator can be more synchronized. Finally, multivariable control has a positive effect in which the success rate of the vertical jumping mechanism is about 80%, and the robot managed to hover on the air for about 7-9 ms.

This paper discusses about analysis the mechanical and forward kinematic of Prosthetic Robot Hand for T-FLoW 3.0, because it is the basic thing in building Prosthetic Robot Hand. This Prosthetic Robot Hand has 15 DoF which represented by 6 motors as the actuator. Mechanism which used for actuating each finger is by twisting the cable. The material used is PLA with 3D printed way for getting mass as light as possible and also easy to install. Mechanical analysis in this paper is to discuss the strength of the finger structure using the static structural analysis method. The kinematics that will be discussed in this paper is Forward Kinematic (FK). In mechanism design, FK is used to find constraint, calculate position vector of End of Efector (EoE). But, this paper only discusses the FK used to be looking for the constraint, it means that how maximum is the point that can be reached by finger with maximum degree of each joint of finger.

Research on T-FloW humanoid robot in EEPIS Robotics Research Center (ER2C) has entered the third generation. Previously, the robot already had primitive motions to mimic 'human-like' walking capabilities by making use of an open loop motion controller. Yet, a feedback control system is required in order to take corrective measures due to walking parameter variations. In this current stage of the work, the development is aimed to provide the robot with adequate number of sensors to detect the movement of the robot. This paper describes the utilisation of the sensors in our robot to analyze and detect its condition when the robot begins to fall down. An inertial measurement unit (IMU) sensor consists of 3-axes accelerometer and 3-axes gyrometer was in use. The analysis was done under V-REP simulation software which is equipped with Vortex dynamic engine. The simulation showed the detected characteristic of the walking parameters of the robot just before it begins to fall down. This simulation result is paramount for further T-FloW walking controller development.

Recently, innovation in the technologies has been driven by the need of a flexible, reconfigurable, and reliable machine for under water operation termed as Remotely Operated Vehicle (ROV). Development of the ROV has opened many opportunities for exploring and make the better understanding of our underwater environment. Degree of freedom is an important aspect in ROV in enabling the flexibility of the movement during its maneuver underwater. This paper proposes the design of a remotely operated underwater vehicle (ROV) with 5 DOF using multi-thrusters configuration. Since the horizontal movement of the proposed ROV needs more flexibility, thus in this design 4 thrusters are situated to handle movement of the ROV in the horizontal plane, and the remaining 2 thrusters are handling the vertical plane movement. To get better understanding about the underwater environment, several sensors are needed to be deployed in the ROV. The proposed ROV design already accommodates the sensors planned to be installed in the vehicle when designing the mechanical model of the ROV. Finally, the proposed mechanical design and the dynamic model of the ROV have been presented for its future development process.

Zero moment point (ZMP) is a mathematical formulation to find a point that causes equilibrium of action and reaction momentum (momentum equal to zero). ZMP can be approached using Single Linear Inverted Pendulum Model (SLIPM). In this paper will explain the modeling of walking trajectory based on the mathematical formulation in SLIPM on the “T-FLoW” humanoid robot. In the SLIPM mathematical equation has 2 main components which are position vector of Center of Mass (CoM) and Acceleration (Linear) of CoM. From these two main compositions, there will be two types of walking trajectory models to be used and implemented in the “T-FLoW” humanoid robot. The first walking locomotion analysis is walking trajectory model the position vector of CoM is dominant. The second walking locomotion analysis is walking trajectory model when the acceleration in CoM is dominant. The results of these two walking trajectory models are for modeling and establishing a control system for robot stability based on dynamic characteristic on both walking trajectory models in the next research.

EEPIS Robotics Research Center (ER2C) has been built a humanoid robot and the name is “T-FLoW” humanoid robot. This Humanoid robot is used to solve the problem in the direct pass during moving ball in the technical challenge RoboCup Competition. This paper will explain about the implementation of direct pass strategy during moving the ball into “T-FloW” humanoid robot. Direct pass strategy is splitting into 3 step. The first step is how to calculate and predict the position, speed, and acceleration during ball movement by using camera vision strategy. The second step is how to doing kick motion when the ball is approaching the foot based on the position, speed, and acceleration from the first step. The third step is the main strategy to combine the first and second step. Based on the experiment result, the success to pass the ball is 80%. The kicking locomotion is not fast enough. Perhaps in next research, the kicking locomotion will be made with fully efficient and faster than before.

In Indonesia research on Humanoid is limited to Kid-Size only, while for Teen-Size is still rare. This encourages teams and researchers to create a Teen-size humanoid called “FLoW”. To perform flexible movements like humans is not easy to do robot. Some of the problems that arise and become the focus of this research is to organize the movement of the robot in order to move, synchronize the movement in every parts of the humanoid robot, mathematical modeling and simulation of robot movement when standing. Taking into account the total kinematics of the humanoid robot, the movement of the robot can be overcome. With forwardinvers kinematics, researchers can determine a movement of the robot by controlling the motor part at a certain point. This section is an actuator of the robot. To do the modeling and simulation using D-H parameter and V-REP simulation software aid. Then for forward-invers kinematics can be implemented on the PID algorithm with the output of the speed on the motor that can form an angle on the motor to drive the robot. The expected result of this research is Humanoid Robot can move to follow the trajectory that has been determined. Making Humanoid Teen-Size robot is expected to increase research on Humanoid Teen-Size in Indonesia. In addition, this FLoW robot can be a supporting material and reference for the development of Humanoid Teen-Size next.

A map of a location made of a human mindset is made briefly by recording a situation already seen in memory. Human behavior is easy to do without a lot of thinking. The process is observed more deeply that when the human mind does not do the behavior in turn like looking at the whole room then just remember, but humans can see at once remember simultaneously. Bringing human behavior into a computer system is done by mimicking how humans look. Looking at using two cameras in combination with the sensor structure. To process the device requires a large computing. Be a challenge for Portable CPU that have lower capabilities than high end CPU. For that humanoid robot can perform tasks simultaneously and can accelerate, especially in image processing using portable CPU required a method that makes the processing into realtime. Achieving realtime with data from previous researcher can not be done with sequential algorithms when the complexity is high. After analyzing the problem was built parallel camera mapping process using multithread algorithm. This paper aims to accelerate the basic process of making the map so as to achieve realtime. This research aims to change the previous process that runs sequentially into a parallel system using multithread algorithm. The results of each process are compared between parallel systems with multithread algorithm and do not use parallel systems. There is a change in speed between the two processes. Further research is concerned with improving the mapping environment results when visualized.