Multimodal layer surveillance map based on anomaly detection using multi‐agents for smart city security

Na, Ki‐In; Chang, Jung Min; Uhm, Taeyoung

doi:10.4218/etrij.2021-0395

Cited by 26 publications

(9 citation statements)

References 30 publications

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“…• Environmental Monitoring: Mobile robots are employed in environmental monitoring tasks such as air and water quality monitoring, weather forecasting, and pollution control, providing more accurate and timely data . • Security and Surveillance: Mobile robots are used for security and surveillance tasks such as perimeter patrol, crowd monitoring, and intrusion detection, providing improved safety and security (Shin et al, 2022). • Entertainment: Mobile robots are used in entertainment, such as theme parks and exhibitions, for tasks such as interactive displays, games, and performances, enhancing the visitor experience (Lin et al, 2023).…”

Section: Mobile Robot Application In 21st Centurymentioning

confidence: 99%

A review of methodologies for path planning and optimization of mobile robots

Sahoo¹,

Choudhury²

2023

J Process Man & New Technol

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This research paper provides a comprehensive review of methodologies for path planning and optimization of mobile robots. With the rapid development of robotics technology, path planning and optimization have become fundamental areas of research for achieving efficient and safe autonomous robot navigation. In this paper, we review the classic and state-of-the-art techniques of path planning and optimization, including artificial potential fields, A* algorithm, Dijkstra's algorithm, genetic algorithm, swarm intelligence, and machine learning-based methods. We analyze the strengths and weaknesses of each approach and discuss their application scenarios. Moreover, we identify the challenges and open problems in this field, such as dealing with dynamic environments and real-time constraints. This paper serves as a comprehensive reference for researchers and practitioners in the robotics community, providing insights into the latest trends and developments in path planning and optimization for mobile robots.

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Section: Mobile Robot Application In 21st Centurymentioning

confidence: 99%

A review of methodologies for path planning and optimization of mobile robots

Sahoo¹,

Choudhury²

2023

J Process Man & New Technol

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“…The multi-modal sensor data can robustly detect objects of interest during not only the day-and nighttime, but also in most weather conditions such as fog and rain. They were able to recognize and respond to abnormal situations, such as fire, illegal parking, noise, and intruders [34].…”

Section: Multi-modal Sensor System Install and Testmentioning

confidence: 99%

Design of Multimodal Sensor Module for Outdoor Robot Surveillance System

et al. 2022

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Recent studies on surveillance systems have employed various sensors to recognize and understand outdoor environments. In a complex outdoor environment, useful sensor data obtained under all weather conditions, during the night and day, can be utilized for application to robots in a real environment. Autonomous surveillance systems require a sensor system that can acquire various types of sensor data and can be easily mounted on fixed and mobile agents. In this study, we propose a method for modularizing multiple vision and sound sensors into one system, extracting data synchronized with 3D LiDAR sensors, and matching them to obtain data from various outdoor environments. The proposed multimodal sensor module can acquire six types of images: RGB, thermal, night vision, depth, fast RGB, and IR. Using the proposed module with a 3D LiDAR sensor, multimodal sensor data were obtained from fixed and mobile agents and tested for more than four years. To further prove its usefulness, this module was used as a monitoring system for six months to monitor anomalies occurring at a given site. In the future, we expect that the data obtained from multimodal sensor systems can be used for various applications in outdoor environments.

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“…The increasing prominence of unmanned aerial vehicles (UAV) and ground vehicles (UGV) has led to the development of diverse applications that require the identification of moving objects. In applications such as video surveillance [1][2][3], aerial monitoring [4][5][6], and autonomous navigation [7][8][9][10][11], the detection of moving objects, such as pedestrians, animals, or small objects, is crucial for intelligent systems. Thus, these expert systems must differentiate between moving and static objects by analyzing continuous video information.…”

Section: Introductionmentioning

confidence: 99%

Background memory‐assisted zero‐shot video object segmentation for unmanned aerial and ground vehicles

Yun,

Kim,

Bae

et al. 2023

ETRI Journal

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Unmanned aerial vehicles (UAV) and ground vehicles (UGV) require advanced video analytics for various tasks, such as moving object detection and segmentation; this has led to increasing demands for these methods. We propose a zero‐shot video object segmentation method specifically designed for UAV and UGV applications that focuses on the discovery of moving objects in challenging scenarios. This method employs a background memory model that enables training from sparse annotations along the time axis, utilizing temporal modeling of the background to detect moving objects effectively. The proposed method addresses the limitations of the existing state‐of‐the‐art methods for detecting salient objects within images, regardless of their movements. In particular, our method achieved mean and values of 82.7 and 81.2 on the DAVIS'16, respectively. We also conducted extensive ablation studies that highlighted the contributions of various input compositions and combinations of datasets used for training. In future developments, we will integrate the proposed method with additional systems, such as tracking and obstacle avoidance functionalities.

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Multimodal layer surveillance map based on anomaly detection using multi‐agents for smart city security

Cited by 26 publications

References 30 publications

A review of methodologies for path planning and optimization of mobile robots

A review of methodologies for path planning and optimization of mobile robots

Design of Multimodal Sensor Module for Outdoor Robot Surveillance System

Background memory‐assisted zero‐shot video object segmentation for unmanned aerial and ground vehicles

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