Enhanced Road Boundary and Obstacle Detection Using a Downward-Looking LIDAR Sensor

Han, Jaehyun; Kim, Dongchul; Lee, Minchae; Sunwoo, Myoungho

doi:10.1109/tvt.2012.2182785

Cited by 160 publications

(76 citation statements)

References 52 publications

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“…4,5,[15][16][17][18][19] To our best of our knowledge, conventional lidar-radar fusion has been mainly focused on detecting moving vehicles, and researches on pedestrian detection have not been investigated yet before. In previous methods, a vehicle is estimated by obtaining its width, length, and shape from lidar and then acquiring its velocity from radar.…”

Section: Lidar-radar Sensor Fusionmentioning

confidence: 99%

Detection scheme for a partially occluded pedestrian based on occluded depth in lidar–radar sensor fusion

et al. 2017

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Son, "Detection scheme for a partially occluded pedestrian based on occluded depth in lidar-radar sensor fusion," Opt. Eng. 56(11), 113112 (2017), doi: 10.1117/1.OE.56.11.113112. Abstract. Object detections are critical technologies for the safety of pedestrians and drivers in autonomous vehicles. Above all, occluded pedestrian detection is still a challenging topic. We propose a new detection scheme for occluded pedestrian detection by means of lidar-radar sensor fusion. In the proposed method, the lidar and radar regions of interest (RoIs) have been selected based on the respective sensor measurement. Occluded depth is a new means to determine whether an occluded target exists or not. The occluded depth is a region projected out by expanding the longitudinal distance with maintaining the angle formed by the outermost two end points of the lidar RoI. The occlusion RoI is the overlapped region made by superimposing the radar RoI and the occluded depth. The object within the occlusion RoI is detected by the radar measurement information and the occluded object is estimated as a pedestrian based on human Doppler distribution. Additionally, various experiments are performed in detecting a partially occluded pedestrian in outdoor as well as indoor environments. According to experimental results, the proposed sensor fusion scheme has much better detection performance compared to the case without our proposed method.

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Section: Lidar-radar Sensor Fusionmentioning

confidence: 99%

Detection scheme for a partially occluded pedestrian based on occluded depth in lidar–radar sensor fusion

et al. 2017

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“…ALS data analysis is time consuming and computer-intensive, depending on the data volume, which in return slows the modeling process in the chain from point to tangible data ready for use in GIS software or similar environments. Many of the approaches concentrate on domain specific solutions which range from DTM creation [9][10][11][12] and geomorphic features detection [2,13,14] to the automatic extraction of buildings [15][16][17][18][19][20][21][22][23], roads [24][25][26][27], and tree reconstruction/tree classification [6,7,[28][29][30][31].…”

Section: Problem Definition and Added Value Of This Review Papermentioning

confidence: 99%

Building Extraction from Airborne Laser Scanning Data: An Analysis of the State of the Art

et al. 2015

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Abstract:This article provides an overview of building extraction approaches applied to Airborne Laser Scanning (ALS) data by examining elements used in original publications, such as data set area, accuracy measures, reference data for accuracy assessment, and the use of auxiliary data. We succinctly analyzed the most cited publication for each year between 1998 and 2014, resulting in 54 ISI-indexed articles and 14 non-ISI indexed publications. Based on this, we position some built-in features of ALS to create a comprehensive picture of the state of the art and the progress through the years. Our analyses revealed trends and remaining challenges that impact the community. The results show remaining deficiencies, such as inconsistent accuracy assessment measures, limitations of independent reference data sources for accuracy assessment, relatively few documented applications of the methods to wide area data sets, and the lack of transferability studies and measures. Finally, we predict some future trends and identify some gaps which existing approaches may not exhaustively cover. Despite these deficiencies, this comprehensive literature analysis demonstrates that ALS data is certainly a valuable source of spatial information for building extraction. When taking into account the short civilian history of ALS one can conclude that ALS has become well established in the scientific community and seems to become indispensable in many application fields.

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“…In Ref. [17], IEPF algorithm is used to identify road features on a high-speed unmanned vehicle which won the championship thereby. We process LADAR data in three steps: The first step is breakpoint detection; the second step is line extraction; the third step is security transformation.…”

Section: Ladar Data Processing For Viability Controlmentioning

confidence: 99%

“…5(b) shows data processing for convex obstacle. The data processing is similar with the traditional IEPF algorithm, see [17]. The algorithm splits scan points P = {p ns , · · · , p n , · · · , p ne } between two continuous breakpoints p ns , p ne into two subsets P = {p ns , · · · , p n } and P " = {p n , · · · , p ns }, when the maximum distance l max from scan points p n in the set P to the line p ns p ne is greater than the threshold l * Th .…”

Section: Line Segment Extractionmentioning

confidence: 99%

Speed Optimization Control for Wheeled Robot Navigation with Obstacle Avoidance Based on Viability Theory

Liu

Gao

2016

Automatika

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Original scientific paperThe navigation efficiency of wheeled robots needs to be further improved. Although related research has proposed various approaches, most of them describe the relationship between the robot and the obstacle roughly. Viability theory concerns the dynamic adaptation of evolutionary systems to the environment. Based on viability, we explore a method that involves robot dynamic model, environmental constraints and navigation control. The method can raise the efficiency of the navigation. We treat the environment as line segments to reduce the computational difficulty for building the viability condition constraints. Although there exists lots of control values which can be used to drive the robot safely to the goal, it is necessary to build an optimization model to select a more efficient control value for the navigation. Our simulation shows that viability theory can precisely describe the link between robotic dynamics and the obstacle, and thus can help the robot to achieve radical high speed navigation in an unknown environment.Key words: Wheeled robot, Navigation, Obstacle avoidance, ViabilityOptimizacija upravljanja brzinom mobilnog robota s izbjegavanjem prepreka zasnovana na teoriji vijabilnosti. Postoji potreba za unaprije enjem učinkovitosti navigacije mobilnih robota. Iako su vezana istraži-vanja predložila različite pristupe, većina ne opisuje precizno odnos izme u robota i prepreke. Teorija vijabilnosti istražuje dinamičke adaptacije evolucijskih sustava njihovoj okolini. Učlanku istražujemo metodu koja može povećati učinkovitost navigacije, zasnovanu na vijabilnosti koja uključuje dinamički model robota, ograničenja okoline robota i samu navigaciju. Radna okolina predstavljena je ravnim crtama kako bi se smanjila računska složenost izgradnje ograničenja. Iako postoji veliki broj iznosa upravljačkih veličina koje bi sigurno uputile robota prema cilju, potrebno je izraditi optimizacijski model koji bi odabrao učinkovitiju upravljačku vrijednost za navigaciju. Izvedene simulacije pokazuju da teorija vijabilnosti može precizno opisati vezu izme u prepreke i dinamike robota te na taj način pomoći robotu da postigne radikalno veće brzine pri navigaciji u nepoznatim prostorima.

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Enhanced Road Boundary and Obstacle Detection Using a Downward-Looking LIDAR Sensor

Cited by 160 publications

References 52 publications

Detection scheme for a partially occluded pedestrian based on occluded depth in lidar–radar sensor fusion

Detection scheme for a partially occluded pedestrian based on occluded depth in lidar–radar sensor fusion

Building Extraction from Airborne Laser Scanning Data: An Analysis of the State of the Art

Speed Optimization Control for Wheeled Robot Navigation with Obstacle Avoidance Based on Viability Theory

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