Robotic Fire Suppression Through Autonomous Feedback Control

McNeil, Joshua G.; Lattimer, Brian Y.

doi:10.1007/s10694-016-0623-1

Cited by 31 publications

(12 citation statements)

References 29 publications

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“…Researchers at Virginia Tech University have carried out a series of studies on fire-fighting robots. The fusion system of infrared stereo vision and LiDAR was used for fire recognition research under different visibility [ 18 , 19 ]. Meanwhile, the infrared stereo was also used for water jet trajectory identification and positioning research.…”

Section: Introductionmentioning

confidence: 99%

An Improved Near-Field Computer Vision for Jet Trajectory Falling Position Prediction of Intelligent Fire Robot

Zhu

Zhao

2020

Sensors

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An improved Near-Field Computer Vision (NFCV) system for intelligent fire robot was proposed that was based on our previous works in this paper, whose aims are to realize falling position prediction of jet trajectory in fire extinguishing. Firstly, previous studies respecting the NFCV system were briefly reviewed and several issues during application testing were analyzed and summarized. The improved work mainly focuses on the segmentation and discrimination of jet trajectory adapted to complex lighting environment and interference scenes. It mainly includes parameters adjustment on the variance threshold and background update rate of the mixed Gaussian background method, jet trajectory discrimination based on length and area proportion parameters, parameterization, and feature extraction of jet trajectory based on superimposed radial centroid method. When compared with previous works, the proposed method reduces the average error of prediction results from 1.36 m to 0.1 m, and the error variance from 1.58 m to 0.13 m. The experimental results suggest that every part plays an important role in improving the functionality and reliability of the NFCV system, especially the background subtraction and radial centroid methods. In general, the improved NFCV system for jet trajectory falling position prediction has great potential for intelligent fire extinguishing by fire-fighting robots.

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Section: Introductionmentioning

confidence: 99%

An Improved Near-Field Computer Vision for Jet Trajectory Falling Position Prediction of Intelligent Fire Robot

Zhu

Zhao

2020

Sensors

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“…One of the ways to reduce the impact of dangerous fire factors on the personnel of operational and rescue units involved in its extinguishing is the use of mobile fire robots [1]. In this case, there are two fundamental possibilities: using the robot in autonomous mode and remote control of it.…”

Section: Introductionmentioning

confidence: 99%

“…In this case, there are two fundamental possibilities: using the robot in autonomous mode and remote control of it. In the first case, based on the analysis of images in the visible and infrared ranges, the com-Engineering bustion area is determined and the fire extinguishing agent is supplied [1]. In the second case, the video image is transmitted to the operator, and it determines the point at which the extinguishing agent should be supplied [2].…”

Section: Introductionmentioning

confidence: 99%

Estimating the Influence of the Wind Exposure on the Motion of an Extinguishing Substance

Abramov

Basmanov

Kryvtsova

et al. 2020

EUREKA: Physics and Engineering

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One of the tasks to be solved when deploying fire extinguishing systems is to determine the range of the fire extinguishing agent supply to the combustion center. This problem is solved using data on the trajectory of the fire-extinguishing agent in the combustion center. The presence of wind impact on the process of supplying a fire extinguishing agent will lead to a change in its trajectory. To take into account wind impact, it becomes necessary to assess the result of such impact. Using the basic equation of dynamics for specific forces, a system of differential equations is obtained that describes the delivery of a fire extinguishing agent to the combustion center. The system of differential equations takes into account the presence of wind impact on the movement of the extinguishing agent. The presence of wind action is taken into account by the initial conditions. To solve such a system, the integral Laplace transform was used in combination with the method of undefined coefficients. The solution is presented in parametric form, the parameter of which is time. For a particular case, an expression is obtained that describes the trajectory of the supply of the extinguishing agent into the combustion center. Nomograms are constructed, with the help of which the operative determination of the estimate of the maximum range of the fire-extinguishing agent supply is provided. Estimates are obtained for the time of delivery of a fire-extinguishing agent to the combustion center, and it is shown that for the characteristic parameters of its delivery, this value does not exceed 0.5 s. The influence of wind action on the range of supply of a fire extinguishing agent is presented in the form of an additive component, which includes the value of the wind speed and the square of the time of its delivery. To assess the effect of wind impact on the movement of the fire extinguishing agent, an analytical expression for the relative error was obtained and it was shown that the most severe conditions for supplying the fire extinguishing agent to the combustion center, the value of this error does not exceed 5.5%. Taking into account the wind effect when assessing the range of supply of a fire-extinguishing agent makes it possible to increase the efficiency of fire-extinguishing systems due to its more accurate delivery to the combustion center

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“…In recent years, computer vision technology has become an important direction in the development of automatic fire suppression systems because it can improve extinguishment efficiency and precision. For example, McNeil [22] proposed an autonomous fire suppression system including a multispectral sensor suite to suppress wood crib fires in indoor environments with high or low visibility. Kim [23] developed a real-time probabilistic classification method for identifying fire, smoke, their thermal reflections, and other objects in infrared images.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Monitoring of Jet Trajectory during Jetting Based on Near-Field Computer Vision

Zhu

et al. 2019

Sensors

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A novel method of near-field computer vision (NFCV) was developed to monitor the jet trajectory during the jetting process, which was used to precisely predict the falling point position of the jet trajectory. By means of a high-resolution webcam, the NFCV sensor device collected near-field images of the jet trajectory. Preprocessing of collected images was carried out, which included squint image correction, noise elimination, and jet trajectory extraction. The features of the jet trajectory in the processed image were extracted, including: start-point slope (SPS), end-point slope (EPS), and overall trajectory slope (OTS) based on the proposed mean position method. A multiple regression jet trajectory range prediction model was established based on these trajectory characteristics and the reliability of the model was verified. The results show that the accuracy of the prediction model is not less than 94% and the processing time is less than 0.88s, which satisfy the requirements of real-time online jet trajectory monitoring.

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Robotic Fire Suppression Through Autonomous Feedback Control

Cited by 31 publications

References 29 publications

An Improved Near-Field Computer Vision for Jet Trajectory Falling Position Prediction of Intelligent Fire Robot

An Improved Near-Field Computer Vision for Jet Trajectory Falling Position Prediction of Intelligent Fire Robot

Estimating the Influence of the Wind Exposure on the Motion of an Extinguishing Substance

Real-Time Monitoring of Jet Trajectory during Jetting Based on Near-Field Computer Vision

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