Geometrical model to drive vision systems with error propagation

Kais, Mikael; Morin, Sandy; Fortelle, Arnaud de La; Laugier, Christian

doi:10.1109/icarcv.2004.1468813

Cited by 6 publications

(2 citation statements)

References 7 publications

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“…Therefore, the heading angle change scriptΔθ calculated by the photoelectric odometer is still used in the improved odometer positioning method. The formulas of the improved odometer positioning method formulas are as follows, where LocationX and LocationY are the coordinates of the delivery robot [25]. scriptΔX=VRob×scriptΔt×cos(α+scriptΔθ2) scriptΔY=VRob×scriptΔt×sin(α+scriptΔθ2) LocationX=LocationX+scriptΔX LocationY=LocationY+scriptΔY…”

Section: Positioning System Designmentioning

confidence: 99%

Design of a Low-Cost Indoor Navigation System for Food Delivery Robot Based on Multi-Sensor Information Fusion

Sun

Guan

Chang

et al. 2019

Sensors

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As the restaurant industry is facing labor shortage issues, the use of meal delivery robots instead of waiters/waitresses not only allows the customers to experience the impact of robot technology but also benefits the restaurant business financially by reducing labor costs. Most existing meal delivery robots employ magnetic navigation technologies, which require magnetic strip installation and changes to the restaurant decor. Once the moving path is changed, the magnetic strips need to be re-laid. This study proposes multisource information fusion, i.e., the fusion of ultra-wide band positioning technology with an odometer and a low-cost gyroscope accelerometer, to achieve the positioning of a non-rail meal delivery robot with navigation. By using a low-cost electronic compass and gyroscope accelerometer, the delivery robot can move along a fixed orbit in a flexible and cost-effective manner with steering control. Ultra-wide band (UWB) and track estimation algorithm are combined by extended Kalman filter (EKF), and the positioning error after fusion is about 15 cm, which is accepted by restaurants. In summary, the proposed approach has some potential for commercial applications.

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Section: Positioning System Designmentioning

confidence: 99%

Design of a Low-Cost Indoor Navigation System for Food Delivery Robot Based on Multi-Sensor Information Fusion

Sun

Guan

Chang

et al. 2019

Sensors

View full text Add to dashboard Cite

show abstract

“…The introduction of artificial beacons in a city is thus not an acceptable solution due to the scale problem. Authors prefer identifying vertical edges which are precisely referenced in GIS ( [2], [5]). Another way consists on the update of the current view with a set of images, recorded and geo-referenced during a calibration phase ( [6], [11]).…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of the road plane with an embedded stereo-rig in urban environments

Simond

2006 IEEE Intelligent Vehicles Symposium

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Abstract-We present in this article an original method to reconstruct the road in the specific context of urban environment thanks to the data provided by an uncalibrated stereo-vision system. The method consists on extracting then tracking features (points, lines) from the road and estimate the homography induced by the plane between two poses. The purposed method copes with the dense traffic conditions: the free space required (first ten meters in front of the vehicle) is slightly equivalent to the security distance between two vehicles. Experimental issues from real data are presented and discussed.

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What can be done with an embedded stereo-rig in urban environments?

Simond

Rives

2008

Robotics and Autonomous Systems

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International audienceThe development of the Autonomous Guided Vehicles (AGVs) with urban applications are now possible due to the recent solutions (DARPA Grand Challenge) developed to solve the Simultaneous Localization And Mapping (SLAM) problem: perception, path planning and control. For the last decade, the introduction of GPS systems and vision have been allowed the transposition of SLAM methods dedicated to indoor environments to outdoor ones. When the GPS data are unavailable, the current position of the mobile robot can be estimated by the fusion of data from odometer and/or Inertial Navigation System (INS). We detail in this article what can be done with an uncalibrated stereo-rig, when it is embedded in a vehicle which is going through urban roads. The methodology is based on features extracted on planes: we mainly assume the road at the foreground as the plane common to all the urban scenes but other planes like vertical frontages of buildings can be used if the features extracted on the road are not enough relevant. The relative motions of the coplanar features tracked with both cameras allow us to stimate the vehicle ego-motion with a high precision. Futhermore, the features which don't check the relative motion of the considered plane can be assumed as obstacles

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Geometrical model to drive vision systems with error propagation

Cited by 6 publications

References 7 publications

Design of a Low-Cost Indoor Navigation System for Food Delivery Robot Based on Multi-Sensor Information Fusion

Design of a Low-Cost Indoor Navigation System for Food Delivery Robot Based on Multi-Sensor Information Fusion

Reconstruction of the road plane with an embedded stereo-rig in urban environments

What can be done with an embedded stereo-rig in urban environments?

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