Accurate and augmented navigation for quadcopter based on multi-sensor fusion

Lekkala, Kiran; Mittal, Vinay Kumar

doi:10.1109/indicon.2016.7838890

Cited by 8 publications

(3 citation statements)

References 26 publications

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“…However, not all the systems provides liner inputted data, for such thing some modification are needed to improve the KF, extended kalamen filter EKF are used for this purpose by linearizing those none liner data, unfortunately this linearization methods, made the EKF complex and making it difficult to implement and quit expensive, not to mentions that it may lead filter to be unstable, however EKF are popular in robotics, navigation application [11] and tracking GPS signals [12].…”

Section: Evaluation Of State Estimate Methodsmentioning

confidence: 99%

A Review of Data Fusion Techniques

Alofi¹,

Alghamdi²,

Alahmadi³

et al. 2017

IJCA

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In many cases, researchers use more than one sensor and synthesize their raw data to generate more meaningful information that can be of greater value than single source data. The process of merging multiple data and knowledge from different sources to represent the object into a regular, accurate, useful, meaningful representation is known as data fusion. This article summarizes the state of data fusion and compares relevant techniques. We explain possible data fusion classifications and review the most common fusion methods such as Kalman filter and The Bayesian Methods. Then we evaluate these methods and discuss the advantages and disadvantages of each method. General TermsMulti-sensor fusion, data fusion, Kalman filter, Particle filter, Bayesian methods, Dempster-Shafer.

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Section: Evaluation Of State Estimate Methodsmentioning

confidence: 99%

A Review of Data Fusion Techniques

Alofi¹,

Alghamdi²,

Alahmadi³

et al. 2017

IJCA

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“…A new self-validating interface was developed for controlling multi-rotor aerial vehicles in single-subject and multi-subject environments. In recent years, multi-rotor aerial vehicles have used in various applications such as monitoring, mapping, person-following [1] and transportation [2]. For a single-subject environment, the proposed method uses right-hand gesture recognition, where a hand in each image frame is detected using an SSD, and a CNN model then performs a classification.…”

Section: Acknowledgmentsmentioning

confidence: 99%

Smart Glove and Hand Gesture-based Control Interface For Multi-rotor Aerial Vehicles

Haratiannejadi

Fard

Šelmić

2019

2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)

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“…An adaptive control-based interface with self-validation for multi-rotor aerial vehicles that recognizes and classifies right and left-hand gestures in a single-subject environment was developed in [4]. The quality of different aspects of life has been increased by using multirotor aerial vehicles in recent years, especially in monitoring and transportation [5].…”

Section: Introductionmentioning

confidence: 99%