Adaptive search control applied to Search and Rescue operations using Unmanned Aerial Vehicles (UAVs)

Chaves, A. N.; Cugnasca, Paulo Sérgio; José, João

doi:10.1109/tla.2014.6948863

Cited by 31 publications

(14 citation statements)

References 11 publications

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“…In parameter learning phase, gradient decent method is used for adjusting initial parameters of antecedent and consequent parts of the new generated rule [26,32,33,38].…”

Section: Parameter Learningmentioning

confidence: 99%

“…This property enables type-2 fuzzy systems to cope with higher levels of uncertainty. Hence, in recent years, there is a great attention to the application of type-2 fuzzy systems in different industrial processes [25,26]. Due to high levels of uncertainty in the structure and parameters of the parallel robots, one dominant industrial application of type-2 fuzzy systems is to control parallel manipulators.…”

Section: Introductionmentioning

confidence: 99%

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Position tracking of a 3-PSP parallel robot using dynamic growing interval type-2 fuzzy neural control

Toloue

Akbarzadeh

et al. 2015

Applied Soft Computing

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“…In parameter learning phase, gradient decent method is used for adjusting initial parameters of antecedent and consequent parts of the new generated rule [26,32,33,38].…”

Section: Parameter Learningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Position tracking of a 3-PSP parallel robot using dynamic growing interval type-2 fuzzy neural control

Toloue

Akbarzadeh

et al. 2015

Applied Soft Computing

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“…Variance is a critical element of robotics and is generally affected by factors such as unpredictable environments, accumulated variance and inaccurate mathematical system modelling [9]. Therefore, it is common practice to integrate multiple sources of information in an attempt to compliment the errors and uncertainties of each source of information [2,10]. This area of robotics is known as sensor fusion, where data acquired from multiple sensors is fused within state estimation algorithms such as the Kalman Filter and its many variants for both linear and nonlinear system models.…”

Section: Introductionmentioning

confidence: 99%

Towards a Model Based Sensor Measurement Variance Input for Extended Kalman Filter State Estimation

Pointon

McLoughlin

Matthews

et al. 2019

Drones

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In this paper, we present an alternate method for the generation and implementation of the sensor measurement variance used in an Extended Kalman Filter (EKF). Furthermore, it demonstrates the limitations of a conventional EKF implementation and postulates an alternate form for representing the sensor measurement variance by extending and improving the characterisation methodology presented in the previous work. As presented in earlier work, the use of surveying grade optical measurement instruments allows for a more effective characterisation of Ultra-Wide Band (UWB) localisation sensors; however, in cluttered environments, the sensor measurement variance will change, making this method not robust. To compensate for the noisier readings, an EKF using a model based sensor measurement variance was developed. This approach allows for a more accurate representation of the sensor measurement variance and leads to a more robust state estimation system. Simulations were run using synthetic data in order to test the effectiveness of the EKF against the originally developed EKF; next, the new EKF was compared to the original EKF using real world data. The new EKF was shown to function much more stably and consistently in less ideal environments for UWB deployment than the previous version.

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“…Thus, the rise of the Unmanned Aerial Vehicles (UAVs) started. Nowadays, there is a wide range of UAVs with multiple sensors and digital cameras that are being used in many different areas such as photogrammetry, agriculture, management of natural resources, mapping and urban planning, rescue [1], assessment and mitigation of disasters, and other Remote Sensing applications [2].…”

Section: Introductionmentioning

confidence: 99%

A Method for Mosaicking Aerial Images based on Flight Trajectory and the Calculation of Symmetric Transfer Error per Inlier

Arteaga¹,

Kemper²,

Bustamante³

et al. 2019

Adv. sci. technol. eng. syst. j.

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In recent years, development of aerial autonomous systems and cameras have allowed increasing enormously the number of aerial images, and their applications in many research areas. One of the most common applications is the mosaicking of images to improve the analysis by getting representations of larger areas with high spatial resolution. This paper describes a simple method for mosaicking aerial images acquired by unmanned aerial vehicles during programmed flights. The images were acquired in two scenarios: a city and a forest in the Peruvian Amazon, for vegetation monitoring purposes. The proposed method is a modification of the automatic homography estimation method using the RANSAC algorithm. It is based on flight trajectory and the calculation of symmetric transfer error per inliers. This method was implemented in scientific language and the performance was compared with a commercial software with respect to two aspects: processing time and geolocation errors. We obtained similar results in both aspects with a simple method using images for natural resources monitoring. In the best case, the proposed method is 6 minutes 48 seconds faster than the compared software and, the root mean squared error of geolocation in X-axis and Y-axis obtained by proposed method are less than the obtained by the compared software in 0.5268 and 0.5598 meters respectively.

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Adaptive search control applied to Search and Rescue operations using Unmanned Aerial Vehicles (UAVs)

Cited by 31 publications

References 11 publications

Position tracking of a 3-PSP parallel robot using dynamic growing interval type-2 fuzzy neural control

Position tracking of a 3-PSP parallel robot using dynamic growing interval type-2 fuzzy neural control

Towards a Model Based Sensor Measurement Variance Input for Extended Kalman Filter State Estimation

A Method for Mosaicking Aerial Images based on Flight Trajectory and the Calculation of Symmetric Transfer Error per Inlier

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