Fuzzy methods for multisensor data fusion

Russo, F.; Ramponi, Giovanni

doi:10.1109/19.293435

Cited by 62 publications

(28 citation statements)

References 18 publications

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“…(5) Fuzzy logic: Fuzzy logic indicates the true degree by specifying a real number between 0 and 1, and it allows uncertain process of multi-sensor information fusion indicated directly in the process of reasoning. It is applicable for a static environment, but need the large amount of calculation [12,13]. (6) Artificial Neural Network: Sensor information can be fusion according to certain learning algorithm, and the network parameters can be get through training, but the choice of sample set is a problem [14].…”

Section: The Main Methods Of Information Fusionmentioning

confidence: 99%

Research on detection system for coal mine detection robot based on the technology of information fusion

Niu

2009

International Technology and Innovation Conference 2009 (ITIC 2009)

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China have a large of coal resources, while the accidents due to gas explosions, gushing water, fire and other factors often happened every year. This paper presents a system of robot's sensors and obstacle avoidance which suitable for detecting mine environmental information. The sensor system that composed of gas sensors, temperature sensors, pressure sensors and obstacle avoidance sensors, enable the robot to finish the detection of mine information successfully and play an important role in taking rescue work favorably. The system of obstacle avoidance is mainly composed of industrial computer and its board. The robot can realize the intelligent and autonomous obstacles-avoiding movement in mine by an advanced navigation technology of fuzzy neural network based on T-S model. The simulation experiments show that this system of sensors can achieve security obstacle avoidance, and detect the information in mine accurately and timely which can support accurate foundation for rescue work.

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Section: The Main Methods Of Information Fusionmentioning

confidence: 99%

Research on detection system for coal mine detection robot based on the technology of information fusion

Niu

2009

International Technology and Innovation Conference 2009 (ITIC 2009)

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“…Histogrammic in motion mapping, Bayesian approach [16] , Kalman filter, Dempster-Shafer theory and fuzzy logic algorithm [17] are four standard multi-sensor fusion approaches applied to path planning of mobile robots. The Bayesian model was used in this work.…”

Section: Map Update Based On Sensor Fusionmentioning

confidence: 99%

Swarm intelligence based dynamic obstacle avoidance for mobile robots under unknown environment using WSN

Han

2008

J. Cent. South Univ. Technol.

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To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In view of moving velocity and direction of both the obstacles and robots, a mathematic model was built based on the exposure model, exposure direction and critical speeds of sensors. Ant colony optimization (ACO) algorithm based on bionic swarm intelligence was used for solution of the multi-objective optimization. Energy consumption and topology of the WSN were also discussed. A practical implementation with real WSN and real mobile robots were carried out. In environment with multiple obstacles, the convergence curve of the shortest path length shows that as iterative generation grows, the length of the shortest path decreases and finally reaches a stable and optimal value. Comparisons show that using sensor information fusion can greatly improve the accuracy in comparison with single sensor. The successful path of robots without collision validates the efficiency, stability and accuracy of the proposed algorithm, which is proved to be better than tradition genetic algorithm (GA) for dynamic obstacle avoidance in real time.

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“…Fuzzy as the mean for the data-fusion have been mostly used as a tool to fuse the data retrieved from multisensor [5], [6] or more recently it is used in fusing position signals from Global Positioning Systems (GPS) and inertial navigation systems (INS) for autonomous mobile vehicles [7]. Moreover, the potential of applying fuzzy logic techniques in traffic and transportation systems analysis and control are also been discussed in few articles [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Towards Realism in an Intelligent Car's Driving Behavior Using Fuzz Inference System

Fouladinejad¹,

Jalil²,

Taib³

et al. 2015

IJCTE

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Fuzzy methods for multisensor data fusion

Cited by 62 publications

References 18 publications

Research on detection system for coal mine detection robot based on the technology of information fusion

Research on detection system for coal mine detection robot based on the technology of information fusion

Swarm intelligence based dynamic obstacle avoidance for mobile robots under unknown environment using WSN

Towards Realism in an Intelligent Car's Driving Behavior Using Fuzz Inference System

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