Quantifying the influence of rain in LiDAR performance

Filgueira, A.; González-Jorge, H.; Lagüela, S.; Díaz-Vilariño, L.; Arias, Pedro

doi:10.1016/j.measurement.2016.10.009

Cited by 132 publications

(91 citation statements)

References 12 publications

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“…The influence of rain for lidar sensors was analyzed in a similar fashion in [6], [12]. Filgueira et al presented a work that quantifies the influence of rain for one lidar sensor and a static scene; in detail the average range, intensity and number of points for certain objects [6]. The results show smaller changes in the distance of detected objects, while the intensity and the number of points decrease dramatically.…”

Section: A Lidar Sensors In Adverse Weather Conditionsmentioning

confidence: 99%

See 1 more Smart Citation

Weather Influence and Classification with Automotive Lidar Sensors

Heinzler

Schindler

Seekircher

et al. 2019

2019 IEEE Intelligent Vehicles Symposium (IV)

159

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Lidar sensors are often used in mobile robots and autonomous vehicles to complement camera, radar and ultrasonic sensors for environment perception. Typically, perception algorithms are trained to only detect moving and static objects as well as ground estimation, but intentionally ignore weather effects to reduce false detections. In this work, we present an in-depth analysis of automotive lidar performance under harsh weather conditions, i.e. heavy rain and dense fog. An extensive data set has been recorded for various fog and rain conditions, which is the basis for the conducted indepth analysis of the point cloud under changing environmental conditions. In addition, we introduce a novel approach to detect and classify rain or fog with lidar sensors only and achieve an mean union over intersection of 97.14 % for a data set in controlled environments. The analysis of weather influences on the performance of lidar sensors and the weather detection are important steps towards improving safety levels for autonomous driving in adverse weather conditions by providing reliable information to adapt vehicle behavior.

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Section: A Lidar Sensors In Adverse Weather Conditionsmentioning

confidence: 99%

“…Lidar sensor performance significantly depends on the environmental conditions as demonstrated in [4], [6], [10]- [14]. Thus, it is fundamental to recognize and quantify the impact of current weather on the lidar performance in order to develop robust perception and thus fusion algorithms.…”

Section: A Lidar Sensors In Adverse Weather Conditionsmentioning

confidence: 99%

Weather Influence and Classification with Automotive Lidar Sensors

Heinzler

Schindler

Seekircher

et al. 2019

2019 IEEE Intelligent Vehicles Symposium (IV)

159

View full text Add to dashboard Cite

show abstract

“…TLS measuring has some limitations, including weather conditions [33], external temperature, vibrations and the ability of materials to reflect. It is impossible to measure reflective surfaces or glass objects (also windows).…”

Section: Introductionmentioning

confidence: 99%

Use of TLS (LiDAR) for Building Diagnostics with the Example of a Historic Building in Karlino

2020

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This article presents the use of TLS (LiDAR) measurement for the evaluation of the technical conditions of a historic building. A FARO M70 laser scanner was used in the study. The measurements was taken as an RCP point cloud. The measurement allowed to partially determine the cause of the building damage. The performed measurement allows to propose a precise solution that could be pre-fabricated. The study shows the usefulness of TLS in building diagnostics. Improper measurement could lead to a wrong solution and a certain degree of uncertainty.

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“…Filgueira et al studied the effects of real rain on LiDAR measurements outdoors [12]. They set up Velodyne VLP-16 outside to measure six areas with different materials and surfaces.…”

Section: Introductionmentioning

confidence: 99%

Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions

2019

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Light detection and ranging sensors (LiDARS) are the most promising devices for range sensing in automated cars and therefore, have been under intensive development for the last five years. Even though various types of resolutions and scanning principles have been proposed, adverse weather conditions are still challenging for optical sensing principles. This paper investigates proposed methods in the literature and adopts a common validation method to perform both indoor and outdoor tests to examine how fog and snow affect performances of different LiDARs. As suspected, the performance degraded with all tested sensors, but their behavior was not identical.

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Quantifying the influence of rain in LiDAR performance

Cited by 132 publications

References 12 publications

Weather Influence and Classification with Automotive Lidar Sensors

Weather Influence and Classification with Automotive Lidar Sensors

Use of TLS (LiDAR) for Building Diagnostics with the Example of a Historic Building in Karlino

Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions

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