Remotely operated vehicle (ROV) plays an important role in the exploration of underwater objects for observation of marine life, oil and gas exploration and rescue. In underwater diving, a variety of factors can influence the movements carried out by ROV such as water flow, water waves, water pressure, etc. Control of balance and depth in the ROV are important factor in carrying out various missions ROV found it in the form of water flow and water waves. PID controller is still ineffective due to the nonlinear nature of the ROV and therefore this paper proposes to add a Fuzzy logic controller to deal with the nonlinearity in the ROV. With a combination of PID and Fuzzy controller, the ROV is able to balance while making the diving and maneuvering moves despite receiving interference in the water. Using the proposed controller, the ROV is able to respond well with respect to disturbances in attitudes and depth motion control scenarios.

This study focuses on the feature extraction and development of tomato growth model. In Indonesia, the application of sensors and actuators to build smart farming has become increasingly popular in the past year but to produce measured harvest quality and quantity in smart farming, a model of growth and yield of the tomato plant is needed. in this paper, observations on the growth of tomato plants were carried out to extract features in the growth of tomato plants. In the experiment, a greenhouse was built to maintain the growth conditions of tomato plants which are equipped with an information system for reading sensor data to determine the greenhouse environment conditions for the growth of tomato plants with a local-global management strategy. from the experiment, we obtained a response model of the tomato plant growth with the effect of the maximum temperature that caused the blossoms to fall. and from the growth model, there are 5 growth stages of tomato plants are obtained, which at each stage has different growth variables with different nutritional needs and environmental conditions. with the important knowledge gained from this experiment, it can be used to develop a dynamic tomato plant growth model based on the growth stage, which is expected to be applied in the control system on smart farming in the future work.

The safety and comfort of a vehicle is very important when driving. One of the security and convenience that can be achieved is to maintain the stable condition of the vehicle when it turns. For this reason a prototype was designed with a control method to control the condition of turning a vehicle. In this paper electronic device system is designed to control turn conditions using the fuzzy logic method, where fuzzy logic processes data error yaw rates and turning angles obtained from the IMU sensor. The system was applied to a three-wheeled vehicle model with a two-wheeled steering system. Based on testing with variations in turning angles and a fixed speed of 20 km / h, the largest yaw rate occurs at a 30 degree turning angle which is 0.2355 rad / s and after being given control of the yaw rate value to 0.03901 rad / s a yaw rate value reduction of 1 , 5943 rad / s. Testing with variations in vehicle speed and fixed turn angle of 10 degrees produces a yaw rate of 0.1314 rad / s and after the control is given to 0.03892 rad / s, a reduction of 0.09248 rad / s occurs. From these tests fuzzy logic is capable of improve vehicle response by minimizing slippage that occurs when the vehicle makes a turn movement so that the three-wheeled vehicle is maintained stability and security.

In human-robot interactions, robots that often interact with humans need some information from humans to be able to communicate. In human-oriented robots, the robots must pay attention wherever the human will go. Therefore, the human-oriented robots are more flexible. To estimate wherever the human will go, it can use the direction of the human or what is called intention. Intention can be taken from the perspective of the human body. An algorithm is needed to estimate the orientation of the human body. In this study, using image processing from depth image is expected to be able to estimate the orientation of the human body when a human is not moving (static orientation) so that it can be used by the robots to predict the intention direction of a human. One method that can be used to classify the orientation of a human body is the Support Vector Machine (SVM) so that it gets a classified orientation value. Then from the classified orientation value to get the static orientation value, Kalman Filter is used. Orientation classification with SVM method has accuracy of 96.528%. Static orientation estimation using this method produces precision value of 0.0970.

Technological innovations in the marine field have developed rapidly in the last decade. One of it is the innovation in the technologies related to the underwater research and exploration. It has been driven by the need of the a flexible, reconfigurable, and reliable machine for underwater operation termed Remotely Operated Vehicle (ROV). The ROV development has opened up many opportunities in the observation and exploration of underwater environment. The most important aspect in the ROV is the flexibility of motion during the maneuver in the water. The mechanical structure and also the static and dynamic analysis is very important aspect in designing ROV related to its operation environment. This paper proposes ROV body design based on analysis characteristic hydrodynamic and buoyancy effect using CFD. The characteristics of each fluid flow affect the motion of the ROV which movement is driven by the thrusters. The hydrodynamic characteristics and buoyancy effect will be analyzed. The result will be used in the further mathematical calculations in the controller design phase.

Recently, 3D visualization technologies such as point cloud are growing rapidly and are in demand for environmental mapping needs because they have the ability to represent the real world in a more complete and in depth way, as well as new and more advanced visual experiences. The point cloud model is able to represent objects well through a series of points and is increasingly used in various fields of research. While 3D visualization technology is growing, several platforms such as humanoid robots, mobile robots, and automatic cars require mapping technology that is able to properly map the surrounding environment with a better display to improve intelligence and decision-making abilities. To overcome the problem of mapping, in this research an experiment was conducted to combine point cloud to form a map based on a visual odometry from stereo camera.

This paper discusses about research for developing human-like robots. To make the robot walk like a human on inclined surface, it is currently being developed into two major parts, namely the mechanical system and the equilibrium motion control system. In this mechanical system, it discusses the relationship of all human parts that are modeled on each joint and link to the robot. The analysis used in modeling this mechanical system is dynamic walking and Dynamic Step for robot on the inclined surface . Whereas for motion control systems on inclined surface, Online Motion Stabilization and Online Posture Stabilization analysis is used. Planning balance movements is used for each joint to make the robot walk stable in inclined surface. Balance system planning is made based on input data obtained from sensor readings from the position of the robot. Then the triple inverse pendulum approach can be used which can be solved by simulating the movement from the feet and body . The Walking Simulation Result have success for dt = 20 ms. It means that the distances and joint values won`t be updated any faster that every 20 ms .

Walking on uneven surface with balanced manner is the key of the humanoid robot. Many essential parameters of the human walking can be captured with seven links planar biped robot. Hence, in this work kinematics, dynamic modeling and trajectory planning of a seven links planar biped robot with six joints, walking on stair with different level ground in the sagital plane. In this paper, the discussion is concerned to control kinematics for dynamic up and down stairs of the humanoid robot with Full-body kinematics based on Zero Moment Point (ZMP) to analyze stability of the bipedal robot. We define that stair configuration is already known. Dynamic of stair climbing is more unstable than dynamic walking on the ground because it needs an additional vertical motion and has different step length of walking. On this kinematics, center of the robot position of mass is adjusted by the upper body of the robot.Trajectory planning based on the behaviour human walking. The validity of the proposed method is confirmed by simulation, using geometry analysis equation and a uniques strategy for ascending and descending stairs. Furthermore Full-body kinematics for analysis has a good result on the simulation experiment with accuracy 100 percent. Position vector from Full-body kinematics will be used to complete the dynamic system model of T-Flow humanoid robot.

The important thing that should be consist on delivery drone is landing speed and dropping object with smoothly. For the two cables and two motor pulley system, balancing control are use to balancing the cable that carrying the gripper, while the speed on landing system are controlled. The main advantage to build the system are using balancing PID controller with cable length input and speed control to makes the pulley automatically landing and pulling the object. The object can be land smoothly with speed control, and the cable will be in stable parallel position when the pulley are rotating with balancing control. To detect the object height, we use the proximity sensor and calibrating with rotary encoder. In this paper, we have installed the speed and balancing control on the two cables pulley-gripper system for delivery drone. The final result, the pulley can be land the box smoothly from 4 - 5 meters distance and stable the cable distance with error less than 2 cm respectively.

The three-dimensional approach in face identification technology had gained prominent significance as the state-of-the-art breakthrough due to its ability to address the currently developing issues of identification technology (illumination, deformation and pose variance). Consequently, this trend is also followed by rapid development of the three-dimensional face identification architectures in which some of them, namely Microsoft Kinect and Intel RealSense, have become somewhat today's standard because of its popularity. However, these architectures may not be the most accessible to all due to its limited customisation nature being a commercial product. This research aims to propose an architecture as an alternative to the pre-existing ones which allows user to fully customise the RGB-D data by involving open source components, and serving as a less power demanding architecture. The architecture integrates Microsoft LifeCam and Structure Sensor as the input components and other open source libraries which are OpenCV and Point Cloud Library (PCL). The result shows that the proposed architecture can successfully perform the intended tasks such as extracting face RGB-D data and selecting out region of interest in the face area.

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.

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.