Obstacle Avoidance Algorithm for Small Autonomous Mobile Robot Equipped with Ultrasonic Sensors

Derkach, Maryna; Matiuk, Danylo; Skarga-Bandurova, Inna

doi:10.1109/dessert50317.2020.9125019

Cited by 12 publications

(7 citation statements)

References 8 publications

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“…The mobile robot can move freely while avoiding obstacles. Maryna Derkach et al [ 36 ] utilized four ultrasonic sensors for obstacle avoidance in mobile robots. Their proposed algorithm uses a linear recursive Kalman filter to process the sensor data, allowing the robot to avoid additional obstacles.…”

Section: Overview Of Single Sensor Sensing Technologiesmentioning

confidence: 99%

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

Liu,

Wang,

Xie

et al. 2024

Sensors

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As a fundamental issue in robotics academia and industry, indoor autonomous mobile robots (AMRs) have been extensively studied. For AMRs, it is crucial to obtain information about their working environment and themselves, which can be realized through sensors and the extraction of corresponding information from the measurements of these sensors. The application of sensing technologies can enable mobile robots to perform localization, mapping, target or obstacle recognition, and motion tasks, etc. This paper reviews sensing technologies for autonomous mobile robots in indoor scenes. The benefits and potential problems of using a single sensor in application are analyzed and compared, and the basic principles and popular algorithms used in processing these sensor data are introduced. In addition, some mainstream technologies of multi-sensor fusion are introduced. Finally, this paper discusses the future development trends in the sensing technology for autonomous mobile robots in indoor scenes, as well as the challenges in the practical application environments.

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Section: Overview Of Single Sensor Sensing Technologiesmentioning

confidence: 99%

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

Liu,

Wang,

Xie

et al. 2024

Sensors

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“…These sensors will act as the robot's eyes and ears so that it can provide insight and understanding of the surrounding environment. Several sensors used for obstacle detection in mobile robots include ultrasonic [24]- [26], lidar [27], [28], and others. The ultrasonic sensor will work by utilizing ultrasonic sound waves emitted and reflected by surrounding objects [24].…”

Section: Journal Of Robotics and Control (Jrc)mentioning

confidence: 99%

Design and Implementation of Fuzzy Logic for Obstacle Avoidance in Differential Drive Mobile Robot

Puriyanto,

Mustofa

2024

Journal of Robotics and Control

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Autonomous mobile robots based on wheel drive are widely used in various applications. The differential drive mobile robot (DDMR) is one type with wheel drive. DDMR uses one actuator to move each wheel on the mobile robot. Autonomous capabilities are needed to avoid obstacles around the DDMR. This paper presents implementing a fuzzy logic algorithm for obstacle avoidance at a low cost (DDMR). The fuzzy logic algorithm input is obtained from three ultrasonic sensors installed in front of the DDMR with an angle difference between the sensors of 45$^0$. Distance information from the ultrasonic sensors is used to regulate the speed of the right and left motors of the DDMR. Based on the test results, the Mamdani inference system using the fuzzy logic algorithm was successfully implemented as an obstacle avoidance algorithm. The speed values of the right and left DDMR wheels produce values according to the rules created in the Mamdani inference system. DDMR managed to pass through a tunnel-shaped environment and reach its goal without hitting any obstacles around it. The average speed produced by DDMR in reaching the goal is 4.91 cm/s.

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“…where FN is the total number of planned errors on the preset path, and R is the proportion of correct points in all the preset path points in the path planning. RMSE [42] is computed by…”

Section: Path Planning Simulation Experimentsmentioning

confidence: 99%

The Path Planning and Location Method of Inspection Robot in a Large Storage Tank Bottom

Wang

Zhu

et al. 2023

Computational Intelligence and Neuroscience

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With the development of robot technology, inspection robots have been applied to the defect detection of large tanks. However, the existing path planning algorithm of the tank bottom detection robot is easy to fall into the local minimum, and the path is not smooth. Besides, the positioning of the tank bottom detection robot is not accurate. This article proposes a path planning and location algorithm for the large tank bottom detection robot. Specifically, we design a preset spiral path according to the shape of the tank bottom, and a rotating potential field (RPF) near the obstacle is added to avoid the problem of path planning falling into a local minimum. We obtained accurate and smooth planning results. Compared with the state-of-the-art, the RPF method reduced the average RMSE by 9.49%. In addition, by measuring the acoustic emission distance, the three-point positioning algorithm can be used to achieve the calculation of the robot position detection in the proposed method, and the average positioning error on the spiral path is only 0.0748 ± 0.0032.

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Obstacle Avoidance Algorithm for Small Autonomous Mobile Robot Equipped with Ultrasonic Sensors

Cited by 12 publications

References 8 publications

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

Design and Implementation of Fuzzy Logic for Obstacle Avoidance in Differential Drive Mobile Robot

The Path Planning and Location Method of Inspection Robot in a Large Storage Tank Bottom

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