Localization and Mapping Using Only a Rotating FMCW Radar Sensor

Vivet, Damien; Checchin, Paul; Chapuis, Roland

doi:10.3390/s130404527

Cited by 84 publications

(50 citation statements)

References 22 publications

(19 reference statements)

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“…The common point to every mobile robot designed to perform SLAM is that they all use exteroceptive sensors. Even if RADAR based SLAM proved to be efficient [44][45][46], we choose to focus our attention in this paper on laser scanning devices. One reason for this choice is that RADAR is not accurate enough yet to provide a good 3D mapping of the surroundings of the vehicle, and so, its fusion with visual sensors is quite difficult.…”

Section: Lidar Based Slammentioning

confidence: 99%

A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping

Debeunne

Vivet

2020

Sensors

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292

114

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Autonomous navigation requires both a precise and robust mapping and localization solution. In this context, Simultaneous Localization and Mapping (SLAM) is a very well-suited solution. SLAM is used for many applications including mobile robotics, self-driving cars, unmanned aerial vehicles, or autonomous underwater vehicles. In these domains, both visual and visual-IMU SLAM are well studied, and improvements are regularly proposed in the literature. However, LiDAR-SLAM techniques seem to be relatively the same as ten or twenty years ago. Moreover, few research works focus on vision-LiDAR approaches, whereas such a fusion would have many advantages. Indeed, hybridized solutions offer improvements in the performance of SLAM, especially with respect to aggressive motion, lack of light, or lack of visual features. This study provides a comprehensive survey on visual-LiDAR SLAM. After a summary of the basic idea of SLAM and its implementation, we give a complete review of the state-of-the-art of SLAM research, focusing on solutions using vision, LiDAR, and a sensor fusion of both modalities.

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Section: Lidar Based Slammentioning

confidence: 99%

A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping

Debeunne

Vivet

2020

Sensors

Self Cite

292

114

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“…Pada penelitan AMR yang pertama dikembangkan metode odometry digabung dengan sensor kamera, penelitian kedua odometry dan sensor ultrasonic LPS (Local Positioning System) serta penelitian ketiga menggabungkan odometry dan Wireless Sensor Network (WSN). Teknologi lain yang saat ini juga dikembangkan untuk sistem navigasi AMR pada area terbatas antara lain kamera [8] dan [9], sonar [10], dan radar [11]. Penelitian ini dapat dijadikan dasar untuk pengembangan kendali berbasis rute menggunakan GPS yang memungkinkan kendaraan mampu mengikuti rute yang areanya lebih luas [12].…”

Section: Pendahuluanunclassified

Robot Mobile Otonom Menggunakan Metode Odometry

Rakhman

Basjaruddin

Susanto

2019

tech

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Robot mobile otonom (autonomous mobile robot, AMR) banyak digunakan baik di industri maupun lingkungan rumah tangga. Robot jenis ini mempunyai kemampuan bergerak menuju tempat tertentu secara otomatis. Penggunaan GPS pada tempat tertutup dan area terbatas belum dapat memenuhi kebutuhan karena keterbatasan resolusi GPS. Pada penelitian ini dikembangkan robot mobile yang mampu menuju titik tertentu dengan memanfaatkan sensor rotary encoder dan metode odometry. Koordinat tujuan diberikan ke robot dan kemudian secara otomatis robot bergerak ke arah titik koordinat tujuan. Pengujian dilakukan dengan memberikan tujuan dengan jarak berbeda yaitu 60 cm, 100 cm, 150 cm, 200 cm, dan 250 cm. Rata-rata galat perhitungan odometry yang dihitung pada jarak tersebut adalah sebesar 0.5 cm, 2.63 cm, 1.65 cm, dan 1.1 cm. Pada pengukuran secara riil didapatkan galat sebesar 7cm, 13cm, 10cm, dan 20 cm. Pengujian rute langsung mempunyai nilai galat yang paling kecil dibanding pengujian rute 1 dan rute 2 yaitu 0,11 cm untuk tujuan x dan 0,25 cm untuk tujuan y. Pada pengukuran posisi riil mempunyai galat x = 3 cm dan y = 2 cm.

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“…The work in [15] is concerned with the use of a mobile ground-based panoramic radar sensor. This is able to deliver both distance and velocity of multiple targets in its surrounding.…”

Section: Papers In the Special Issuementioning

confidence: 99%

Introduction to the Special Issue on “New Trends towards Automatic Vehicle Control and Perception Systems”

Milanés

Bergasa

2013

Sensors

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Intelligent and automatic systems are making our daily life easier. They are able to automate tasks that, up to now, were performed by humans, freeing them from these tedious tasks. They are mainly based on the classical robotic architectures where the stages of perception-using different sensor sources or even a fusion of a set of them-and planning-where intelligent control systems are applied-play a key role. Among all of the fields in which intelligent systems can be applied, transport systems are considered one of the most promising ones since over one million fatalities-including drivers, pedestrians, cyclists and motorcyclists-are registered each year worldwide and they can definitively help to reduce these figures.The growth in the number of drivers in the last decades, and consequently in the number of vehicles, has made traffic accidents become a major concern in the road transportation sector. Solutions such as building new transport infrastructures-specifically in urban areas where space limitations make it almost impossible-or increasing fines for inappropriate driving have not achieved the goal of reducing the number of fatalities, either in urban environments or highways. New policies on the part of the Governments are focused on the development of a safer, more reliable and more efficient transportation supported by intelligent systems.The field of research in which all these topics fall into is well-known as intelligent transportation systems (ITS). ITS focuses on improving road safety by acting on two possible aspects: on the one hand, the infrastructure and the possibilities of optimizing traffic flow, and on the other hand, acting on the cars with the development of Advanced Driver Assistance Systems (ADAS) and the possibilities of optimizing traffic safety. The final goal is trying to reduce the number of collisions, or at least to mitigate their consequences. In this connection, one of the currently hot topics in the road OPEN ACCESS

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Localization and Mapping Using Only a Rotating FMCW Radar Sensor

Cited by 84 publications

References 22 publications

A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping

A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping

Robot Mobile Otonom Menggunakan Metode Odometry

Introduction to the Special Issue on “New Trends towards Automatic Vehicle Control and Perception Systems”

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