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All Journal Emerging Science Journal Journal of Robotics and Control (JRC)
Maharani Raharja, Nia
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Environmental Science Mechanical Engineering

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Journal : Emerging Science Journal

 1 
PID-based with Odometry for Trajectory Tracking Control on Four-wheel Omnidirectional Covid-19 Aromatherapy Robot Iswanto, .; Ma'arif, Alfian; Maharani Raharja, Nia; Supangkat, Gatot; Arofiati, Fitri; Sekhar, Ravi; Uddin Rijalusalam, Dhiya
Emerging Science Journal Vol. 5 (2021): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SPER-13

Abstract

Inhalation therapy is one of the most popular treatments for many pulmonary conditions. The proposed Covid-19 aromatherapy robot is a type of Unmanned Ground Vehicle (UGV) mobile robot that delivers therapeutic vaporized essential oils or drugs needed to prevent or treat Covid-19 infections. It uses four omnidirectional wheels with a controlled speed to possibly move in all directions according to its trajectory. All motors for straight, left, or right directions need to be controlled, or the robot will be off-target. The paper presents omnidirectional four-wheeled robot trajectory tracking control based on PID and odometry. The odometry was used to obtain the robot's position and orientation, creating the global map. PID-based controls are used for three purposes: motor speed control, heading control, and position control. The omnidirectional robot had successfully controlled the movement of its four wheels at low speed on the trajectory tracking with a performance criterion value of 0.1 for the IAEH, 4.0 for MAEH, 0.01 for RMSEH, 0.00 for RMSEXY, and 0.06 for REBS. According to the experiment results, the robot's linear velocity error rate is 2%, with an average test value of 1.3 percent. The robot heading effective error value on all trajectories is 0.6%. The robot's direction can be monitored and be maintained at the planned trajectory. Doi: 10.28991/esj-2021-SPER-13 Full Text: PDF
IoT-based Lava Flood Early Warning System with Rainfall Intensity Monitoring and Disaster Communication Technology Suwarno, Iswanto; Ma'arif, Alfian; Maharani Raharja, Nia; Nurjanah, Adhianty; Ikhsan, Jazaul; Mutiarin, Dyah
Emerging Science Journal Vol. 4 (2020): Special Issue "IoT, IoV, and Blockchain" (2020-2021)
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SP1-011

Abstract

A lava flood disaster is a volcanic hazard that often occurs when heavy rains are happening at the top of a volcano. This flood carries volcanic material from upstream to downstream of the river, affecting populous areas located quite far from the volcano peak. Therefore, an advanced early warning system of cold lava floods is inarguably vital. This paper aims to present a reliable, remote, Early Warning System (EWS) specifically designed for lava flood detection, along with its disaster communication system. The proposed system consists of two main subsystems: lava flood detection and disaster communication systems. It utilizes a modified automatic rain gauge; a novel configured vibration sensor; Fuzzy Tree Decision algorithm; ESP microcontrollers that support IoT, and disaster communication tools (WhatsApp, SMS, radio communication). According to the experiment results, the prototype of rainfall detection using the tipping bucket rain gauge sensor can measure heavy and moderate rainfall intensities with 81.5% accuracy. Meanwhile, the prototype of earthquake vibration detection using a geophone sensor can remove noise from car vibrations with a Kalman filter and measure vibrations in high and medium intensity with an accuracy of 89.5%. Measurements from sensors are sent to the webserver. The disaster mitigation team uses data from the webserver to evacuate residents using the disaster communication method. The proposed system was successfully implemented in Mount Merapi, Indonesia, coordinated with the local Disaster Deduction Risk (DDR) forum. Doi: 10.28991/esj-2021-SP1-011 Full Text: PDF
Co-Authors Adhianty Nurjanah Alfian Ma’arif Arofiati, Fitri Dyah Mutiarin, Dyah Iswanto, . Jazaul Ikhsan Sekhar, Ravi Sugiyarta Sugiyarta Supangkat, Gatot Suwarno, Iswanto Uddin Rijalusalam, Dhiya