Precise localization for achieving next-generation autonomous navigation: State-of-the-art, taxonomy and future prospects

Shit, Rathin Chandra

doi:10.1016/j.comcom.2020.06.007

Cited by 17 publications

(5 citation statements)

References 161 publications

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“…It is believed that it is currently impossible to build an autonomous vehicle that can navigate in all conditions (SAE level 5), because weather conditions affect the data received from sensors of such a vehicle too much [2,24,25,33,38]. A single drop of water on a camera lens can scatter light blurring the camera's field of view.…”

Section: Impact Of Adverse Weather Conditions On the Performance Of S...mentioning

confidence: 99%

Problems related to the operation of autonomous vehicles in adverse weather conditions

BRZOZOWSKI¹,

Parczewski²

2023

Combustion Engines

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Article introduces and discusses the sensors used in autonomous cars. The reliability of these devices is crucial for the proper operation of autonomous driving systems. The research works related to the issue of the performance of autonomous sensors in adverse weather conditions is discussed and critically analysed. The negative effects caused by bad weather conditions are characterised. The paper presents the result of author's own research concern on the effects of rain, snow and fog on lidar measurments. The results obtained are presented, detailing the most important threats from each weather phenomenon. Attempts currently being made to address these issues are presented as well. The paper concludes with a summary of the research results, the current state of knowledge and suggestions for future developments.

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Section: Impact Of Adverse Weather Conditions On the Performance Of S...mentioning

confidence: 99%

Problems related to the operation of autonomous vehicles in adverse weather conditions

BRZOZOWSKI¹,

Parczewski²

2023

Combustion Engines

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“…Bazując na tych danych, działają algorytmy i systemy odpowiedzialne za jazdę i bezpieczeństwo. Obecnie, stworzenie pojazdu autonomicznego, który mógłby poruszać się w nieznanym terenie przy niesprzyjających warunkach pogodowych (deszcz, śnieg, mgła) wciąż stanowi duże wyzwanie [55,2,36,37,47]. Woda jest w stanie zalegać na obiektywie i zamazywać obraz, a strugi deszczu rozpraszają i wchłaniają światło wiązki lasera [22].…”

Section: Wstępunclassified

Wpływ Niekorzystnych Warunków Atmosferycznych Na Działanie Sensorów Wykorzystywanych W Samochodach Autonomicznych

BRZOZOWSKI¹,

Parczewski²

2021

Projektowanie, Badania I Eksploatacja

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Streszczenie: Celem artykułu jest objaśnienie wpływu niekorzystnych warunków pogodowych na najbardziej popularne sensory wykorzystywane w samochodach autonomicznych. W pracy przedstawiono typowe sensory takie jak: kamera, LiDAR oraz RADAR, a następnie wskazano zakłócenia jakie w ich pracy wywołują niekorzystne warunki pogodowe. Przedstawiono wpływ: deszczu, śniegu oraz mgły. Ponadto omówiono próby zmierzające do ograniczenia tego wpływu. Proponowane działania dotyczą zarówno usprawnień samego sprzętu jak i rozwijania metod analizy obrazu. Podsumowaniem opracowania jest konkluzja, że najlepsze efekty otrzymuje się podczas wykorzystywania różnych sensorów, które mogą się wzajemnie uzupełniać.

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“…Even the approaches are based on Wi-Fi or Bluetooth Low Energy (BLE) in terms of wireless radio frequency (RF) signal positioning methods [5][6][7]. To consider the cost and complexity of constructing positioning systems with these technologies, it is still impossible to overcome the impact of human body shadowing effects on positioning accuracy and stability [8,9].…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, it is necessary to consider such factors as the environmental impact of the technologies, costs, ease of development and maturity of the technologies. Therefore, for improving the location accuracy, integrating the multi-sensor information with sensor fusion approaches of positioning systems is a worth-study strategic issue [5,8,9,23,24].…”

Section: Introductionmentioning

confidence: 99%

Research on calibration‐free fingerprinting positioning techniques based on terrestrial magnetism databases for indoor environments

Yeh

Lai

Tsai

et al. 2022

IET Radar Sonar & Navi

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Location‐based services (LBSs) in such indoor places as museums, airport terminals, and train stations are becoming more and more popular among smartphone users. Hence, the research on indoor positioning technologies is increasing. Indoor positioning technologies using Wi‐Fi or Bluetooth wireless signals have some problems that cannot be overcome, for example, inconsistent data caused by human body shadowing effects. Positioning accuracy and stability still need to be improved to provide higher quality LBS applications. Smartphones have built‐in geomagnetic and acceleration sensors, and the Earth's magnetic field is not affected by human body shadowing effects, so it increases the appeal of using geomagnetism to enable indoor positioning with smartphones. This article proposed approaches in light of calibration‐free fingerprinting positioning techniques with terrestrial magnetism databases for indoor environments. For the differences in measurements yielded by various mobile phone (MP) models and brands, adjustments can be made using the ratio of the total intensity of the magnetic field and its horizontal component to correct the discrepancies. Finally, with the arrangement of four landmarks, the average error distance of the research results in the experimental environment is 3.59 m. The average accuracy of the k‐nearest neighbour (k‐NN) mobile phones is 71.3%.

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Precise localization for achieving next-generation autonomous navigation: State-of-the-art, taxonomy and future prospects

Cited by 17 publications

References 161 publications

Problems related to the operation of autonomous vehicles in adverse weather conditions

Problems related to the operation of autonomous vehicles in adverse weather conditions

Wpływ Niekorzystnych Warunków Atmosferycznych Na Działanie Sensorów Wykorzystywanych W Samochodach Autonomicznych

Research on calibration‐free fingerprinting positioning techniques based on terrestrial magnetism databases for indoor environments

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