Reliability prediction of single crystal silicon MEMS using dynamic Raman spectroscopy

Phd ThesisThe work investigates an extension and improvement to reliability prediction in single crystal silicon MEMS by utilising dynamic Raman spectroscopy to allow fracture test data collected directly from devices thereby taking account of actual geometrical tolerances, dynamic load conditions and effects from the microfabrication process. Micro-cantilever beam MEMS devices microfabricated from (100) crystalline silicon wafers having [110] beam direction were used in this experiment. A piezo actuator was used to vibrate the devices. The fracture data was taken by increasing the supply voltage to bring each device to rupture whilst a continuous beam HeNe laser was directed from the [100] direction to particular positions on the sample allowing for capture of the photons. The resulting Raman profile, broadened by the vibration of the device, was fit using a Voigt profile and compared to the no load condition. A calibration step was used to convert the Raman signal to volumetric μstrain. The reliability prediction methodology used in this work was developed under the Weibull distribution function that is based on the concept of weakest link theory describing distribution of flaws in brittle material. As each device was fabricated from semiconductor grade single crystalline silicon, it can be considered to have no mechanical defects with the flaws on the device only existing as surface flaws induced from the microfabrication process during manufacturing. Differently processed surfaces each have their own Weibull parameters. The failure prediction of a particular MEMS device is calculated from these parameters with the simulated structure responses due to applied load being predicted from the finite element package ANSYS. The failure prediction method shows a good agreement with the experimental results with accuracy of 10%. However, visual observations were necessary as a number of ruptured specimens started to fail from the bottom side of the clamped end and propagated through [111] direction so from the upper side the failure looks like it started from a distance from the clamped end. The experimental work was carried out utilising [100] Raman scattering. This limits the ability of the system to only capture the strain condition in one direction; the other strain directions were approximated using silicon orthotropic material properties and assuming that the load is a uniaxial load. This limitation forces the failure prediction distribution function to treat silicon as an isotropic material with the strength ii characteristic scale parameter in the Weibull distribution being the same value for all directions. This limitation together with extending the work towards implementing an “off-axis” Raman characterisation able to characterise all the strain directions is discussed for future work

Stereo vision-based obstacle avoidance module on 3D point cloud data

This paper deals in building a 3D vision-based obstacle avoidance and navigation. In order for an autonomous system to work in real life condition, a capability of gaining surrounding environment data, interpret the data and take appropriate action is needed. One of the required capability in this matter for an autonomous system is a capability to navigate cluttered, unorganized environment and avoiding collision with any present obstacle, defined as any data with vertical orientation and able to take decision when environment update exist. Proposed in this work are two-step strategy of extracting the obstacle position and orientation from point cloud data using plane based segmentation and the resultant segmentation are mapped based on obstacle point position relative to camera using occupancy grid map to acquire obstacle cluster position and recorded the occupancy grid map for future use and global navigation, obstacle position gained in grid map is used to plan the navigation path towards target goal without going through obstacle position and modify the navigation path to avoid collision when environment update is present or platform movement is not aligned with navigation path based on timed elastic band method

Transformed Stereo Vision and Structure Sensor for Development 3D Mapping on "FLoW" Humanoid Robot in Real Time

In this paper, we proposed a method for building 3D Mapping environment in real time. The purpose of this model is to be able to approach the human ability to quickly know the environment. The problem of building a 3D mapping in real time is dependent on the efficiency of the algorithm to transform 2D images into depth data forms, which then transformed into a 3D model. This paper shows a method of transformation which has built an efficient algorithm because it can complete the entire sequential algorithm in real time. The algorithm has successfully run the whole system that only has a depth pixel error average of 18,10% and an average error of the system running in real time

Velocity control of ROV using modified integral SMC with optimization tuning based on Lyapunov analysis

Remotely Operated Vehicle also known as ROV is a vehicle with high nonlinearity and uncertainty parameters that requires a robust control system to maintain stability. The nonlinearity and uncertainty of ROV are caused by underwater environmental conditions and by the movement of the vehicle. SMC is one of the control systems that can overcome nonlinearity and uncertainty with the given robust system. This work aims to control velocity of the vehicle with proposes the use of modified integral SMC compensate error in ROV and the use of particle swarm optimization (PSO) to optimize the adjustment of SMC parameters. The ROV used in this paper has a configuration of six thrusters with five DoF movements that can be controlled. Modified integral sliding mode is used to control all force direction to increase the convergence of speed error. Adjustment optimization techniques with PSO are used to determine four values of sliding control parameters for five DoF. Using Lyapunov stability approach control law of sliding mode is derived and its global stability proved mathematically. Simulation results are conducted to evaluate the effectiveness of Modified Integral SMC and compared with nonlinear control

Kinematics modeling of six degrees of freedom humanoid robot arm using improved damped least squares for visual grasping

The robotic arm has functioned as an arm in the humanoid robot and is generally used to perform grasping tasks. Accordingly, kinematics modeling both forward and inverse kinematics is required to calculate the end-effector position in the cartesian space before performing grasping activities. This research presents the kinematics modeling of six degrees of freedom (6-DOF) robotic arm of the T-FLoW humanoid robot for the grasping mechanism of visual grasping systems on the robot operating system (ROS) platform and CoppeliaSim. Kinematic singularity is a common problem in the inverse kinematics model of robots, but. However, other problems are mechanical limitations and computational time. The work uses the homogeneous transformation matrix (HTM) based on the Euler system of the robot for the forward kinematics and demonstrates the capability of an improved damped least squares (I-DLS) method for the inverse kinematics. The I-DLS method was obtained by improving the original DLS method with the joint limits and clamping techniques. The I-DLS performs better than the original DLS during the experiments yet increases the calculation iteration by 10.95%, with a maximum error position between the end-effector and target positions in path planning of 0.1 cm

Gerak Robot Berkaki Dua menggunakan ROS dan RViz sebagai Visualisasi Interaktif

ABSTRAKPengembangan sistem operasi pada bidang robotika telah menjadi fokus utama pada era ini. Salah satu perkembangan sistem operasi pada teknologi robot saat ini adalah Robot Operating System (ROS) dengan RViz. ROS merupakan sistem operasi berbasis library dan beberapa tools untuk mengembangkan suatu program pada robot, sedangkan RViz merupakan visualisasi tiga dimensi yang dapat digunakan untuk memvisualisasikan robot dan data sensor dynamixel. Pada Penelitian kali ini, peneliti membuat simulasi beberapa gerakan yang dilakukan pada RViz dan kemudian diimplementasikan pada robot. Tingkat keberhasilan dari perencanaan gerakan ini memiliki rata rata error sebesar 1.8%. Gerakan condong ke kiri memiliki rata-rata error sebesar 0.83%. Gerakan condong ke kanan memiliki rata-rata error sebesar 0.84%. Gerakan mengangkat satu kaki memiliki rata-rata error sebesar 1.71%. Gerakan kaki kanan ke depan memiliki rata-rata error sebesar 3.83%.Kata kunci: Robot Berkaki Dua, Robot Operating System (ROS), RViz (rosvisualization), Dynamixel Controller, Data Sensor Dynamixel. ABSTRACTThe development of operating systems in the field of robotics has become the main focus of this era. One of the operating system developments in robot technology today is the Robot Operating System (ROS) with RViz. ROS is a library-based operating system and several tools for developing a program on robots, while RVIZ is a three-dimensional visualization that can be used to visualize robots and dynamixel sensor data. In this study, researchers made a simulation of some of the movements carried out on RViz and then implemented on robots. The success rate of planning this movement has an average error of 1.8%. Leaning to the left has an average error of 0.83%. Leaning to the right has an average error of 0.84%. One leg lift has an average error of 1.71%. The movement of the right foot forward has an average error of 3.83%.Keywords: Biped Robot, Robot Operating System (ROS), RViz (Ros-Visualization), Dynamixel Controller, Sensor Dynamixel Data

Sistem Multi Agen untuk Pelayanan Drone pada Groundbase Docking Station

ABSTRAKMulti-Agent System (MAS) diajukan sebagai solusi untuk mengatasi permasalahan pada groundbase sebuah DDS, di mana pada groundbase terdapat AGV yang bertugas untuk membantu Drone beraktifitas di DDS hingga kemudian berangkat kembali menuju DDS lain. Metode auction serta contract antar agent digunakan dalam pemrosesan request dari Drone dan pembagian sumber daya. Pada MAS diterapkan algoritma prioritas sebagai solusi apabila terjadi konflik antar agen. Pengujian dengan simulasi pada CoppeliaSim dan ROS (Robot Operating System) menunjukkan bahwa penggunaan algoritma prioritas berdampak positif pada MAS yang dibuat. Pada DDS dengan skenario 11 AGV, terjadi peningkatan kemampuan DDS dalam menerima dan memproses request yang datang dari 57.9% menjadi 100%, serta pemecahan deadlock yang terjadi pada DDS dari 10 menjadi 0 sehingga seluruh request dapat terselesaikan.Kata kunci: Multi-Agent System, Algoritma Prioritas, Drone Docking Station, AGV ABSTRACTThe Multi-Agent System (MAS) was proposed as a solution to overcome problems in the groundbase of a DDS, where on the groundbase there is an AGV whose job is to help drones carry out activities in DDS and then depart for another DDS. Auction methods and contracts between agents are used in processing requests from drones and sharing resources. In MAS, a priority algorithm is applied as a solution in the event of a conflict between agents. Tests with simulations on CoppeliaSim and ROS (Robot Operating System) show that the use of priority algorithms has a positive impact on the created MAS. In DDS with 11 AGV scenario, there is an increase in DDS ability to receive and process incoming requests from 57.9% to 100%, as well as solving deadlocks that occur in DDS from 10 to 0 so that all requests can be resolved.Keywords: Multi-Agent System, Priority Algorithm, Drone Docking Station, AG

Rule-Based Learning untuk Robot Humanoid T-FLoW Belajar Berjalan

ABSTRAKRiset tentang penggunaan learning dalam motion robot humanoid telah banyak dilakukan di seluruh dunia. Salah satunya adalah melakukan learning gerakan berjalan pada robot. Penelitian ini akan menjelaskan suatu metode learning “Rule Based” yang simple dan cepat dalam menemukan solusi gerakan berjalan yang stabil pada robot humanoid T-FLoW . Robot diibaratkan seperti anak kecil yang belajar berjalan, dia tahu cara berjalan, akan tetapi tidak tahu seberapa besar dia harus menggerakkan sendi-sendi atau joint di kakinya agar dapat berjalan seimbang. Oleh karena itu sistem learning akan menemukan nilai point-point trayektori yang cocok untuk berjalan dengan stabil. Dengan menggunakan software simulasi CoppeliaSim, kami menerapkan metode tersebut. Hasilnya, robot humanoid T-FLoW dapat berjalan dengan stabil sejauh 170 langkah hanya dengan melakukan learning sebanyak 400 episode.Kata kunci: Robot humanoid T-FLoW, Rule-Based Learning, Learning, CoppeliaSim, Trayektori. ABSTRACTResearch about the use of learning in motion of humanoid robot has been done in many countries. One of them was done by learning a stable walking gait in humanoid robot. This research will explain a fast and simple Rule Based learning method to find the solution of stable walking motion for T-FLoW humanoid robot. A robot was assumed like a child trying to walk, he knows how to walk, but doesn’t know how much he has to move his legged joints to get a stable walking. So, our learning system will find those trajectory point values that is suitable to walk stably. By using CoppeliaSim software, we implement our method. The result is, T-FLoW humanoid robot was able to walk stably for about 170 steps with only 400 episodes of learning.Keywords: T-FLoW humanoid robot, Rule-Based Learning, Learning, CoppeliaSim, Trajectory

Teen-Size Humanoid “FLoW†Complete Analytical Kinematics

Humanoid research in Indonesia is quite a lot, but in reality only limited in kid-size proportional size, while for the Teen-Size is still rare. Research on the Teen-Size Humanoid robot requires more joints to be able to perform the movement compared to the size of Kid-Size, therefore required more complex modeling to determine the movement. With complete kinematics anlysis, the movement of the robot can be solved. With kinematic forward-invers, researchers can determine the movement of robots by controlling the motor parts that function as a joint on the robot. In this study, the modeling uses D-H parameter, because this modeling has been widely used, besides the calculation can be solved by computing. And then for the simulation can be done with V-REP software. Forward-invers kinematics can be implemented on the PID algorithm, in order to generate speed on the motor that can form an angle on the motor to make the movement. The result of this research is to obtain equation of matrix transformation from all body parts of robot. With the creation of this Humanoid Teen-Size robot, it is hoped that the research on Humanoid robot in Indonesia will be increasingly diverse and increasing, and can be used as a support and reference in the development of Humanoid Teen-Size next

Analisis Kinematika dan Pola Gerakan Berjalan pada Robot Bipedal Humanoid T-FLoW 3.0

ABSTRAK Robot humanoid merupakan robot menyerupai manusia dengan tingkat kompleksitas yang tinggi dan fungsi yang serbaguna. Pada penelitian ini dilakukan analisis model kinematika gerak pada robot bipedal humanoid TFLoW 3.0, serta menganalisis pola gerakan berjalannya. Pola pergerakan yang diimplementasikan pada robot bipedal TFLoW 3.0 merupakan hasil pendekatan dari teori cara berjalan manusia dengan menggunakan enam gerakan dasar manusia saat berjalan. Kemudian menganalisis model gerakan robot menggunakan kinematika terbalik dengan solusi geometri. Tujuan dari model kinematika terbalik adalah untuk mengubah data input berupa posisi kartesian menjadi nilai sudut untuk setiap parameter joint pada masing-masing Degrees of Freedom (DoF). Lalu dilakukan analisis model mekanik robot saat berjalan yang terbagi atas fase tegak dan fase berayun yang bertujuan untuk mengetahui hasil pengujian. Kata kunci: robot humanoid, gaya berjalan, kinematika, TFLoW, DoF.   ABSTRACT Humanoid robots are human-like robots with a high level of complexity and versatile functions. In this study, kinematics analyze on TFLoW 3.0 humanoid bipedal robot is carried out, as well as analyzing the pattern of its walking movement. The implemented movement of TFLoW 3.0 bipedal robot is the result of an approach from human walk using six basic human movements when walking. the robot movement model is analyzed by inverse kinematics with geometric solutions. Invers kinematics model is to transform the input data in the form of a Cartesian position into an angle value for each joint parameter in each Degrees of Freedom (DoF). Then an analysis of the robot's mechanical model when walking is carried out which is divided into a stance phase and a swinging phase which aims to determine the test results. Keywords: humanoid robot, gait, kinematics, TFLoW, DoF