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All Journal Perfecting a Video Game with Game Metrics Sinergi Proceeding of the Electrical Engineering Computer Science and Informatics TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer Jurnal Abdi Masyarakat (JAM) Journal FORTEI-JEERI International Journal of Engineering Continuity

Suwoyo, Heru

Universitas Mercu Buana

Author-ID : 1175658

Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

Published : 18 Documents Claim Missing Document

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The Role of Block Particles Swarm Optimization to Enhance The PID-WFR Algorithm Heru Suwoyo; Abdurohman Abdurohman; Yifan Li; Andi Adriansyah; Yingzhong Tian; Muhammad Hafizd Ibnu Hajar
International Journal of Engineering Continuity Vol. 1 No. 1 (2022): ijec
Publisher : Sultan Publisher

In the conventional Proportional Integral Derivation (PID) controller, the parameters are often adjusted according to the formulas and actual application. However, this empirical method will bring two disadvantages. First, testing the program takes much time and usually needs help to reach the optimal solution. Second, the PID parameters will not adapt to the new environment when the situation changes. This paper proposed a method by employing a Block Particles Swarm Optimization (BPSO) to enhance the conventional Proportional Integral Derivation (PID) algorithm to overcome the mentioned disadvantages. The genetic algorithm (GA) first optimized the PID parameters. However, its optimization time is relatively long. Then, a Block Particle Swarm Optimization (BPSO) algorithm is designed to solve the problem of long optimization time. This method was then applied to the wall-following robot problem by realistically simulating it to confirm the performance. After Compared with conventional methods, the proposed method shows a relatively stable solution.

Performance of a Wall-Following Robot Controlled by a PID-BA using Bat Algorithm Approach Heru Suwoyo; Ferryawan Harris Kristanto
International Journal of Engineering Continuity Vol. 1 No. 1 (2022): ijec
Publisher : Sultan Publisher

A wall-following robot needs a controller that applies the closed-loop concept to move actively without hindrance. Some controllers with good capabilities can act as controllers for wall follower robots, such as PID controllers. Conceptually, this controller's good performance depends on tuning the three gains before use. Instead of giving the expected and appropriate output, wrong settings will provide inaccuracies for the controller, so applying the manual method at the tuning stage is not recommended. For this reason, PID controllers are often implemented in a system supported by appropriate optimization methods, such as Genetic Algorithm or Particle Swarm Optimization. Furthermore, different from this, in this study, the Bath Algorithm is used as an alternative optimization algorithm. Its application begins with a realistic simulation of a wall-following robot. This is done to provide the possibility to implement online PID controllers and BAs. In the end, several methods are compared to find out the performance of this type of approach. Moreover, based on the observed comparative results, the proposed method gives a better value in accumulative error and convergence speed in the PID optimization process.

A Mixed Fast-RRT*-A* To Solve the Problem of Generating Nodes near Obstacles for Optimal Paths Heru Suwoyo; Raudah Alfiani
International Journal of Engineering Continuity Vol. 1 No. 2 (2022): ijec
Publisher : Sultan Publisher

In the robot environment with static obstacles, robots designed to avoid obstacles and move from the initial position to the destination position, the consumption of the minimum value and the search for the shortest path as the current research, most of the studies are based on obstacle detection to search for more than one path planning. The path using path planning has two sampling methods based on which by working according to random nodes while searching based on using heuristics to find the path. Fast-RRT*-A* were to optimize a path with fast time intensity. From Fast-RRT* developed with improvement-RRT with optimal fast, namely fast optimal in an unreachable space from random trees introduced for speed and algorithm stability; (2) Random steering is used in expansion to solve performance problems in tight spaces; (3) Path fusion path adjustments are obtained quickly. The results of this study are in the form of a profit map comparing the three PRC algorithms* with a time of 48.6474, A* with a time of 38.7527, and FastRRT*-A* with a time of 10.1411, So these three steps make Fast- RRT*-A*.

Utilizing Inverse Kinematics for Precise Guidance in Planning 6-DoF Robot End-Effector Movements Heru Suwoyo; Andi Adriansyah; Julpri Andika; Muhammad Hafizd Ibnu Hajar; Thathit Gumilar Triwidya Mochtar; Muhammad Yusuf; Fajri Rezki Hutomo
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.148

The solution of the kinematic inverse determines a substantial part of the robotic arm's control accuracy. Researchers frequently employ standard problem-solving techniques such as numerical, algebraic, iterative, and geometric methods. Although geometric like trigonometrical method has been widely studied, and their application is strongly dependent on the shape and dimensions of the robot. The complexity of the steps makes this approach difficult for researchers. In order to give a clearance and easiness, the step-by-step features of inverse kinematics are described in this research. The study begins with forward kinematics and refers to the DH-parameter in Homogeneous Matrix Transformations calculation. The existence of specific elements applied to mathematical derivation constituted the basis of forward kinematic discussions. And based on geometrical analysis, the inverse kinematic is then derived. Furthermore, simulations are performed to demonstrate the actual implementation of IK and the solution is then used to initiate the path planning process.

Dubin’s Curve of RRT* Merged With A* Heru Suwoyo; Fahrudin Fahrudin
International Journal of Engineering Continuity Vol. 1 No. 1 (2022): ijec
Publisher : Sultan Publisher

One of the fundamental problems in mobile robotics is a robot path planning of the mobile robot through its environment. Path planning problem for the mobile robot with differential constraints using modified RRT (Rapidly exploring random tree) algorithm based on Dubin’s curves. the planning problem is considered as a problem of finding a feasible path between the initial and goal point in a static environment with obstacles. This process can be conducted either using local information from sensors or by emloying global a-priori known information about robot’s environment. The problem is how to generate a path from the beginning to the destination point gradually during movement using modified RRT (Rapidly exploring random tree) algorithm based on Dubin’s curves. Combining the dubin curve RRT* algorithm with A* is a new method that can calculate the entire path from the starting point of the destination before moving using global information about the map. The purpose of making the path is to make it easier for the operator to determine the path that must be traversed by the robot. The way the robot works is to read the line made by the operator using matlab based on the map, then matlab will calculate the distance of the path to be traversed using an algorithm from the star point to the goal point. Based on the simulation results that have been carried out this method is more efficient when compared to the RRT* or A* algorithms. because this algorithm can produce a path with the shortest path with a fast time to get to the destination point without crashing into obstacles. By adding a new algorithm to find a new path optimally to get a path that is close to optimal by combining and adjusting several feasible paths and also adding a searching-based algorithm, namely A* combined with Dubin Curve- RRT* is sampling based, where the A* algorithm has a function heuristic used to increase the cost and time of searching.

Review Paper: Key Points on Robot Navigation and Its Practical Uses in the Field of Manufacturing Heru Suwoyo; Julpri Andika; Taufik Hidayat
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.227

Key aspects are covered in this review article, along with a brief explanation of mobile robot navigation and its uses in the industrial sector. This study emphasizes the significance of robot navigation in enhancing productivity, efficiency, and safety in manufacturing processes by compiling important ideas from the body of research and literature. This study investigates several robot navigation algorithms and strategies, from simple algorithms to sophisticated ones like SLAM (Simultaneous Localization and Mapping). This study also examines particular issues and concerns about the application of robot navigation systems in industrial settings, such as path planning, obstacle avoidance, and worker cooperation. This paper presents some noted applications of robot navigation, such as material handling, assembly, quality control, and logistics, using case studies and examples. The conversation also touches on new developments and prospective paths for robot navigation technology, highlighting the possibility for more innovation and connection with Industry 4.0 projects. All things considered, this review article is an invaluable tool for scholars, practitioners, and business experts who want to comprehend the function of robot navigation in contemporary manufacturing processes and how it will affect industrial automation in the future.

Co-Authors Abdurohman Abdurohman Adriansyah, Andi Andi Adriansyah Andi Adriansyah Andi Adriansyah Andi Adriansyah Andi Adriansyah Chenwei Deng Deng, Chenwei Fahrudin Fahrudin Fajri Rezki Hutomo Febriandirza, Arafat Fengfeng Xi Ferryawan Harris Kristanto Guangjie Yuan Hossain, Md Musabbir Ibnu Hajar, Muhammad Hafizd Julpri Andika Julpri Andika Ketty Siti Salamah Li, Long Long Li Long Li Md Musabbir Hossain Muhammad Hafizd Ibnu Hajar Muhammad Hafizd Ibnu Hajar Muhammad Hafizd Ibnu Hajar Muhammad Hafizd Ibnu Hajar Muhammad Hafizd Ibnu Hajar Muhammad Hafizd Ibnu Hajar Muhammad Yusuf Prastika Indriyanti Rachmat Muwardi Raudah Alfiani Taufik Hidayat Thathit Gumilar Triwidya Mochtar Thong, Zhou Tian, Yingzhong Tian, Yingzhong Tong Zhou Triyanto Pangaribowo Wang, Wenbin Wenbin Wang Wenbin Wang Yifan Li Yingzhong Tian Yingzhong Tian Yingzhong Tian Yingzhong Tian Yingzhong Tian Yudhi Gunardi Zendi Iklima Zhou Thong

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