Room Mapping using Ultrasonic Range Sensor on the ATRACBOT (Autonomous Trash Can Robot): A Simulation Approach

Haq, Faris Atoil; Dewantara, Bima Sena Bayu; Marta, Bayu Sandi

doi:10.1109/ies50839.2020.9231734

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…The system determined distances based on Time of Flight (ToF) measurements, considering the propagation speed of the sonic wave in the medium. Several studies uses this type of sensor for measuring waste level in dumpsters [28,29].…”

Section: Ultrasonic Sensormentioning

confidence: 99%

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Node Assembly for Waste Level Measurement: Embrace the Smart City

Brito

Tuesta

Lima

et al. 2022

Communications in Computer and Information Science

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Municipal Solid Waste Management Systems (MSWMS) worldwide are currently facing pressure due to the rapid growth of the population in cities. One of the biggest challenges in this system is the inefficient expenditure of time and fuel in waste collection. In this regard, cities/municipalities in charge of MSWMS could take advantage of information and communication technologies to improve the overall quality of their infrastructure. One particular strategy that has been explored and is showing interesting results is using a Wireless Sensors Network (WSN) to monitor waste levels in real-time and help decision-making regarding the need for collection. The WSN is equipped with sensing devices that should be carefully chosen considering the real scenario in which they will work. Therefore, in this work, three sets of sensors were studied to evaluate which is the best to be used in the future WSN assembled in Bragança, Portugal. Sets tested were HC-SR04 (S1), HC-SR04 + DHT11 (S2), and US-100 (S3). Tests considered for this work were air temperature and several distances. In the first, the performance of each set to measure a fixed target (metal and plastic box) was evaluated under different temperatures (1.7 -37 ℃). From these results, two best sets were further used to assess distance measurement at a fixed temperature. This test revealed low absolute errors measuring the distances of interest in this work, ranging from 0.18% to 1.27%.

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Section: Ultrasonic Sensormentioning

confidence: 99%

“…In solid waste management system, no work using this sensor was found. In fact, literature on this device had to be searched outside the database used in previous sections, and most of the works found were dealing with robotic applications [29].…”

Section: Ultrasonic Sensormentioning

confidence: 99%

Node Assembly for Waste Level Measurement: Embrace the Smart City

Brito

Tuesta

Lima

et al. 2022

Communications in Computer and Information Science

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“…The Telegram botbased application is able to send and receive information between the robot and the officer. The navigation system [7] is developed in the form of simulation, and the robot has not been implemented directly.…”

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confidence: 99%

Improved Performance of Trash Detection and Human Target Detection Systems using Robot Operating System (ROS)

Kisron

Dewantara

Oktavianto

2021

JRE

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In a visual-based real detection system using computer vision, the most important thing that must be considered is the computation time. In general, a detection system has a heavy algorithm that puts a strain on the performance of a computer system, especially if the computer has to handle two or more different detection processes. This paper presents an effort to improve the performance of the trash detection system and the target partner detection system of a trash bin robot with social interaction capabilities. The trash detection system uses a combination of the Haar Cascade algorithm, Histogram of Oriented Gradient (HOG) and Gray-Level Coocurrence Matrix (GLCM). Meanwhile, the target partner detection system uses a combination of Depth and Histogram of Oriented Gradient (HOG) algorithms. Robotic Operating System (ROS) is used to make each system in separate modules which aim to utilize all available computer system resources while reducing computation time. As a result, the performance obtained by using the ROS platform is a trash detection system capable of running at a speed of 7.003 fps. Meanwhile, the human target detection system is capable of running at a speed of 8,515 fps. In line with the increase in fps, the accuracy also increases to 77%, precision increases to 87,80%, recall increases to 82,75%, and F1-score increases to 85,20% in trash detection, and the human target detection system has also improved accuracy to 81%, %, precision increases to 91,46%, recall increases to 86,20%, and F1-score increases to 88,42%.

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