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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol
Putra Wisnu Agung Sucipto
Universitas Negeri Malang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Potential Field Obstacle Avoidance Powered by Grid Certainty Map and Minimum Histogram Rahmat Zidan; Amalia Prameswari Alvina; Putra Wisnu Agung Sucipto
TELKA - Telekomunikasi Elektronika Komputasi dan Kontrol Vol 12 No 1 (2026): TELKA
Publisher : Jurusan Teknik Elektro UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/telka.v12n1.66-78

Abstract

An omnidirectional robot moving in a crowd of robot soccer players requires autonomous navigation to navigate moving obstacles, generate safe, smooth, and adaptive trajectories when global information is unavailable. Global navigation and local control must be integrated so that spatial memory can balance speed, safety, and smoothness. This study proposes the implementation of Potential Field Obstacle Avoidance (PFOA) with a grid certainty map and a minimum histogram to address these challenges. This idea is based on the repulsive and attractive forces that shape the decision of the direction of motion in PFOA, which need to be accompanied by the confidence of the empty space map in the distribution of obstacle histograms that direct the robot to the right direction. Based on experiments that have been conducted, this approach has proven to perform better than the hybrid A* and bug methods. Our proposed algorithm is able to make the robot's travel time to the target consistently 13-21 seconds, with a smooth motion trajectory due to sharp maneuvers in the most difficult areas that are minimal, and the best safety confidence level value based on the certainty value between the two comparison methods. So it can be concluded that the strengthened PFOA is able to adapt to local dynamics and is superior in planning global robot trajectory maps that contain obstacles.
Blanket Pixel-Based Segmentation for Detecting Object Geometry Putra Wisnu Agung Sucipto; Danang Arengga Wibowo; Annisa Firasanti; Muhammad Amin Bakri; Khusnul Yaqin
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10727

Abstract

This study aims to develop a blanket pixel-based approach to construct object geometry for image segmentation. Object geometry can be formed from a collection of pixels generated from the edge detection process. However, edge pixels that will be included in a segment must go through an identification process to determine their identity, with a reference segment as a reference for labeling. This work proposes the terminology of blanket pixels, namely pixels that surround a pixel that does not yet have an identity due to being isolated from the surrounding segments, as a spatial exoskeleton for the labeling process. This approach has been tested, and the results show that we successfully detect the structure of tilapia egg circles with clear fortifications when the scanning radius parameter is set to 10 pixels and the proximity between the surrounding pixels and the labeled pixels is 11.8 pixels. Out of 114 egg circles, this method successfully detected 105 eggs, with 9 small eggs (2–3 pixels in diameter) undetected, resulting in a detection ratio of 92.11%. The blanket pixel approach effectively recognizes and reclassifies isolated pixel labels. This approach supports the process of labeling pixels in areas with significant ambiguity.
Co-Authors Amalia Prameswari Alvina Annisa Firasanti Danang Arengga Wibowo Khusnul Yaqin Muhammad Amin Bakri Rahmat Zidan