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All Journal Sinergi Jurnal Teknologi Elektro InComTech: Jurnal Telekomunikasi dan Komputer Minda Baharu Jurnal Abdi Masyarakat (JAM) Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal for Social Responsibility Jurnal Abdidas International Journal of Advanced Technology in Mechanical, Mechatronics and Material (IJATEC) Journal of Integrated and Advanced Engineering (JIAE) Journal of Community Service International Journal of Engineering Continuity
Julpri Andika
Universitas Mercu Buana
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Journal : Sinergi

 1 
ANALYSIS OF KINEMATIC FOR LEGS OF A HEXAPOD USING DENAVIT-HARTENBERG CONVENTION Luo Qingsheng; Julpri Andika
SINERGI Vol 22, No 2 (2018)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (443.044 KB) | DOI: 10.22441/sinergi.2018.2.001

Abstract

The headway of manipulator robots makes the development of a hexapod quite fast. Unfortunately, a hexapod is unstable to moving in a regular movement with some values added to programming algorithms. Various techniques implemented yet to the algorithms, like entering the degree values of each servo. However, to simplify the implementation of the algorithms, need some equations. This paper offered a hexapod control system based on Arduino that using Denavit-Hartenberg parameters to produce the equations. Various experiments have performed. Based on the experiments the offered system able to simplify the programming algorithms.
Problem solving path planning and path tracking in a 3 DOF hexapod robot using the RRT* algorithm with path optimization and Pose-to-Pose Suwoyo, Heru; Burhanudin, Achmad; Tian, Yingzhong; Andika, Julpri
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.007

Abstract

Path planning is one of the most fundamental problems that must be solved before a robot can navigate and explore autonomously. Path planning needs to be integrated with path tracking to be applied to autonomous robots. This makes path tracking also important for autonomous robot navigation which cannot be separated from path planning. There are two path planning methods, the first is search-based method, the second is sampling-based method. Both have their own advantages, but the popular and commonly used sampling-based algorithm due to its fast convergence is preferred in path planning.  The RRT* algorithm was developed. This improvement initiated a major civilization in sampling-based algorithms, namely parent node selection and rewiring in RRT. Although there has been an improvement in optimality, RRT* still doesn't provide the distance optimality value as expected, due to its character that is still adopted from RRT.  The resulting path is still suboptimal and not smooth (jagged). On the other side, Path tracking has several methods, however, these path tracking methods are difficult to apply to autonomous robots and need to be adapted to the robot used. Based on the description above, there are still problems with path planning, namely paths that are still less than optimal and convergence that is still slow.  This research will add a way to shorten the distance in the RRT* algorithm with the triangular inequality method.  Meanwhile, for path tracking, we will apply the pose-to-pose method, which follows the waypoint that has been made by path planning.
A Bidirectional-RRT*-Connect-Assisted RRT*-Smart for a path planning algorithm Suwoyo, Heru; Hastomi, Yudi; Andika, Julpri
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.017

Abstract

Although Rapidly Exploring Random Tree Star (RRT*) has been considered to be able to achieve convergence to an optimal solution, this method has a slow convergence speed and requires an infinite amount of time to produce a truly optimal solution. For this reason, RRT*-Smart which includes path optimization and intelligent sampling processes was introduced. Although the addition of these methods can directly complete infinite-duration RRT* searches, they will work once the initial path obtained with RRT* is available. The effectiveness of reducing the optimality time is determined by the initial path formed. If this path is not close to optimal, the path optimization and intelligent sampling process will take a long time, and vice-versa. For this reason, RRT*-Connect, which has the advantage of searching from two directions, is proposed in this study. The goal is to replace the RRT* algorithm to produce a more optimal initial formed path. Based on this approach, this method will be named Connect-RRT*-Smart. Several methods, such as RRT, RRT*, RRT*-Connect, and RRT*-Smart, are compared to see their performance in producing the feasible path. Regarding this comparative result, the proposed method shows better performance in terms of convergence speed and path optimality. 
Design of path planning robot simulator by applying sampling based method Suwoyo, Heru; Andika, Julpri; Adriansyah, Andi
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.016

Abstract

This research aims to create a simulator for solving the global path planning of mobile robots. Various sampling-based methods such as Rapidly-exploring Random Tree (RRT), RRT*, and Fast-RRT, along with other derivative algorithms, have been widely used to solve path-planning problems in mobile robots. The level of computational efficiency, path optimality, and the ability to adapt to variant environments are some of the issues that still arise, although these techniques have shown good results in many cases. Although the existing solutions are innovative, comparison between the existing methods is still difficult due to significant differences in convergence speed, implementation complexity, and quality of the resulting paths. This makes choosing the most suitable method for a particular application difficult. The simulator uses sampling-based path planning algorithms such as RRT*, Fast RRT*, RRT*-Smart, informed-RRT*, and Honey Bee Mating Optimization-based Fast-RRT*. With this simulator, users can easily compare the performance of each algorithm and see the characteristics and efficiency of each algorithm in various situations. By running all methods through this simulator, the user can easily compare the methods based on convergence speed and optimality. Therefore, it will effectively help users understand robot navigation, improve the quality of learning, and promote the development of path-planning technology for mobile robots.
Co-Authors Adi Juliyanto Akhmad Wahyu Dani Akhmad Zakky Andi Adriansyah Andika Arrizki Angela Dirman Annisa Hakim Zamzami Burhanudin, Achmad Coto Julianto Dafit Feriyanto Dinata, Rizky Elly Yuliawati Erna Setiany Fadli Sirait Fina Supegina Harun Usman Ghifarsyam Hastomi, Yudi Hongmin Gao Hutomo, Fajri Rezki Imelda Uli Vistalina Jibran, Alwan Ketty Siti Salamah Kusuma, Hiero Loura Meilita Saragih Simarmata Luo Qingsheng M. Hafiz Ibnu Hajar Melinda Utami Mirna Yunita Muhammad Hafizd Ibnu Hajar Muhammad Yusuf Pratiwi, Riri Putra, Firoos Safana Qingsheng, Luo Rachmat Muwardi Rahayu, Muthia Ramadhan, Kurnia Ramadhan, Muhamad Husen Rizki Briandana Said Attamimi Setiyo Budiyanto Shamsudin, Abu Ubaidah Suwoyo, Heru Taufik Hidayat Tian, Yingzhong Triwidya Mochtar, Thathit Gumilar Triyanto Pangaribowo Yananto Mihadi Putra Yayu Lestari Yudhi Gunardi Yudhi Gunardi Zendi Iklima