Ground vehicle navigation in harsh urban conditions by integrating inertial navigation system, global positioning system, odometer and vision data

Kim, S.-B.; Bazin, Jean-Charles; Lee, H.-K.; Choi, Kyoung-Ho; Park, S.-Y.

doi:10.1049/iet-rsn.2011.0100

Cited by 66 publications

(46 citation statements)

References 16 publications

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“…In the scenario of vehicle/robot navigation in outdoor environments, a different positioning method should be employed. Sensors, such as GPS, inertial measurement units, LIDAR, and cameras, have been employed for this purpose [1,2,7], as described in the introduction section. …”

Section: Methodsmentioning

confidence: 99%

“…Localization is an important function in navigation. The sensors generally used in the positioning system of autonomous vehicles include Global Positioning Systems (GPS), inertial measurement units, Light Detection and Ranging (LIDAR), and camera sensors [1,2]. When lane markings are available, lane-detection systems, based on LIDAR [3], and/or cameras [4,5], can provide lateral distance measurements from the lane markings to the vehicle for lane-level navigation [6].…”

Section: Introductionmentioning

confidence: 99%

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Navigation of an Autonomous Wheeled Robot in Unknown Environments Based on Evolutionary Fuzzy Control

Chou

Juang

2018

Inventions

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Navigation of a wheeled robot in unknown environments is proposed in this paper. The approach may be applied to navigating an autonomous vehicle in unknown environments, such as parking lots. The navigation consists of three parts: obstacle avoidance behavior, target seeking behavior, and a behavior supervisor. The obstacle avoidance behavior is achieved by controlling the robot to move along an obstacle boundary through evolutionary fuzzy control. In the evolutionary fuzzy control approach, a Pareto set of fuzzy controllers (FCs) is found though a multi-objective continuous ant colony optimization algorithm. Target seeking behavior is achieved by controlling the robot through hybrid proportional-integral-derivative (PID) controllers. The behavior supervisor determines the switching between obstacle avoidance and target seeking behaviors, where the dead-cycle problem is considered. Simulations and experiments were performed to verify the effectiveness of the proposed navigation scheme.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Navigation of an Autonomous Wheeled Robot in Unknown Environments Based on Evolutionary Fuzzy Control

Chou

Juang

2018

Inventions

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“…While the cameras are low-priced, the precision of relative positioning using the images is high as compared with other navigation sensors. Furthermore, we can easily obtain image sequences during driving, hybrid approaches using images for positioning also seem to be promising (Soloviev and Venable, 2010;Kim et al, 2011;Yoo et al, 2005, Kim et al, 2004Goldshtein et al, 2007). Single camera or more cameras' images are used with GPS data to enhance the positioning accuracy in many studies.…”

Section: Indrodouctionmentioning

confidence: 99%

Improving Car Navigation With a Vision-Based System

Kim

Choi

Lee

2015

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The real-time acquisition of the accurate positions is very important for the proper operations of driver assistance systems or autonomous vehicles. Since the current systems mostly depend on a GPS and map-matching technique, they show poor and unreliable performance in blockage and weak areas of GPS signals. In this study, we propose a vision oriented car navigation method based on sensor fusion with a GPS and in-vehicle sensors. We employed a single photo resection process to derive the position and attitude of the camera and thus those of the car. This image georeferencing results are combined with other sensory data under the sensor fusion framework for more accurate estimation of the positions using an extended Kalman filter. The proposed system estimated the positions with an accuracy of 15 m although GPS signals are not available at all during the entire test drive of 15 minutes. The proposed vision based system can be effectively utilized for the low-cost but high-accurate and reliable navigation systems required for intelligent or autonomous vehicles.

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“…Combined measurement methods are also widely used [13][14][15][16][17]. Ideally, the position error is meterlevel and the orientation error exceeds 0.3° outdoors.…”

Section: Introductionmentioning

confidence: 99%

Omnidirectional angle constraint based dynamic six-degree-of-freedom measurement for spacecraft rendezvous and docking simulation

Shi

Yang

Lin

et al. 2018

Meas. Sci. Technol.

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In this paper we present a novel omnidirectional angle constraint based method for dynamic 6-DOF (six-degree-of-freedom) measurement. A photoelectric scanning measurement network is employed whose photoelectric receivers are fixed on the measured target. They are in a loop distribution and receive signals from rotating transmitters. Each receiver indicates an angle constraint direction. Therefore, omnidirectional angle constraints can be constructed in each rotation cycle. By solving the constrained optimization problem, 6-DOF information can be obtained, which is independent of traditional rigid coordinate system transformation. For the dynamic error caused by the measurement principle, we present an interpolation method for error reduction. Accuracy testing is performed in an 8 × 8 m measurement area with four transmitters. The experimental results show that the dynamic orientation RMSEs (root-mean-square errors) are reduced from 0.077° to 0.044°, 0.040° to 0.030° and 0.032° to 0.015° in the X, Y, and Z axes, respectively. The dynamic position RMSE is reduced from 0.65 mm to 0.24 mm. This method is applied during the final approach phase in the rendezvous and docking simulation. Experiments under different conditions are performed in a 40 × 30 m area, and the method is verified to be effective.

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Ground vehicle navigation in harsh urban conditions by integrating inertial navigation system, global positioning system, odometer and vision data

Cited by 66 publications

References 16 publications

Navigation of an Autonomous Wheeled Robot in Unknown Environments Based on Evolutionary Fuzzy Control

Navigation of an Autonomous Wheeled Robot in Unknown Environments Based on Evolutionary Fuzzy Control

Improving Car Navigation With a Vision-Based System

Omnidirectional angle constraint based dynamic six-degree-of-freedom measurement for spacecraft rendezvous and docking simulation

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