Motion Constraints and Vanishing Point Aided Land Vehicle Navigation

Liu, Zhenbo; El‐Sheimy, Naser; Yu, Chunyang; Yong-yuan, Qin

doi:10.3390/mi9050249

Cited by 19 publications

(14 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…R k is the covariance matrix of the measurement noise, describes the uncertainty of the observations. When the forward velocity updates v b =[v MF 0 0] T (for example mass airflow velocity updates) are applied to the navigation filter, the observation model and the design matrix are described in Equations (15) and (16)…”

Section: Integration Schemementioning

confidence: 99%

“…Odometers [ 10 ], magnetometers [ 11 ], ultrasonic sensors [ 12 ], light detection and ranging (LIDAR) [ 13 ], radio detection and ranging (RADAR) [ 14 ], and cameras [ 15 ] are examples of the aiding sensors that can be used for aiding INS. Moreover, land vehicle motion constraints can also be applied to aid the INS during GNSS signal outages [ 16 ]. Non-holonomic constraints (NHC), Zero velocity UPdaTe (ZUPT), and Zero Integrated Heading Rate (ZIHR) [ 17 ] are examples of the motion constraints.…”

Section: Introductionmentioning

confidence: 99%

“…Vision sensor is used in land vehicles as environmental awareness. Vision can also contribute in the navigation solution either by vision-based [ 31 ] or vision-aided navigation system [ 16 ]. Visual odometry (VO) is based on the camera motion estimation between successive images [ 32 ], where it is implemented by using a single vision sensor or stereo cameras [ 33 ].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optical and Mass Flow Sensors for Aiding Vehicle Navigation in GNSS Denied Environment

Moussa

Zahran

Mostafa

et al. 2020

Sensors

Self Cite

View full text Add to dashboard Cite

Nowadays, autonomous vehicles have achieved a lot of research interest regarding the navigation, the surrounding environmental perception, and control. Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) is one of the significant components of any vehicle navigation system. However, GNSS has limitations in some operating scenarios such as urban regions and indoor environments where the GNSS signal suffers from multipath or outage. On the other hand, INS standalone navigation solution degrades over time due to the INS errors. Therefore, a modern vehicle navigation system depends on integration between different sensors to aid INS for mitigating its drift during GNSS signal outage. However, there are some challenges for the aiding sensors related to their high price, high computational costs, and environmental and weather effects. This paper proposes an integrated aiding navigation system for vehicles in an indoor environment (e.g., underground parking). This proposed system is based on optical flow and multiple mass flow sensors integrations to aid the low-cost INS by providing the navigation extended Kalman filter (EKF) with forward velocity and change of heading updates to enhance the vehicle navigation. The optical flow is computed for frames taken using a consumer portable device (CPD) camera mounted in the upward-looking direction to avoid moving objects in front of the camera and to exploit the typical features of the underground parking or tunnels such as ducts and pipes. On the other hand, the multiple mass flow sensors measurements are modeled to provide forward velocity information. Moreover, a mass flow differential odometry is proposed where the vehicle change of heading is estimated from the multiple mass flow sensors measurements. This integrated aiding system can be used for unmanned aerial vehicles (UAV) and land vehicle navigations. However, the experimental results are implemented for land vehicles through the integration of CPD with mass flow sensors to aid the navigation system.

show abstract

Section: Integration Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optical and Mass Flow Sensors for Aiding Vehicle Navigation in GNSS Denied Environment

Moussa

Zahran

Mostafa

et al. 2020

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…Given that visual sensor is a passive sensor and does not rely on any external equipment except ambient light, one of the most important features of visual navigation is the autonomy. With the improvement of computational capabilities, visual navigation can be applied to many important applications in various fields, for instance, robot navigation [1], unmanned aerial vehicles [2], and virtual or augmented reality.…”

Section: Introductionmentioning

confidence: 99%

A Novel Fault-Tolerant Navigation and Positioning Method with Stereo-Camera/Micro Electro Mechanical Systems Inertial Measurement Unit (MEMS-IMU) in Hostile Environment

et al. 2018

View full text Add to dashboard Cite

Visual odometry (VO) is a new navigation and positioning method that estimates the ego-motion of vehicles from images. However, VO with unsatisfactory performance can fail severely in hostile environment because of the less feature, fast angular motions, or illumination change. Thus, enhancing the robustness of VO in hostile environment has become a popular research topic. In this paper, a novel fault-tolerant visual-inertial odometry (VIO) navigation and positioning method framework is presented. The micro electro mechanical systems inertial measurement unit (MEMS-IMU) is used to aid the stereo-camera, for a robust pose estimation in hostile environment. In the algorithm, the MEMS-IMU pre-integration is deployed to improve the motion estimation accuracy and robustness in the cases of similar or few feature points. Besides, a dramatic change detector and an adaptive observation noise factor are introduced, tolerating and decreasing the estimation error that is caused by large angular motion or wrong matching. Experiments in hostile environment showing that the presented method can achieve better position estimation when compared with the traditional VO and VIO method.

show abstract

“…As we know, an initial navigation system (INS) should carry out the initial alignment before its normal work, such as measuring velocity, attitude, and position [1], when the initial attitude will be determined.…”

Section: Introductionmentioning

confidence: 99%

Research on In-Flight Alignment for Micro Inertial Navigation System Based on Changing Acceleration using Exponential Function

Yun

Zhou

2018

Micromachines

View full text Add to dashboard Cite

In order to guarantee the stable flight of a guided projectile, it is difficult to realize in-flight alignment for the micro inertial navigation system (MINS) during its short flight time. In this paper, a method based on changing acceleration using exponential function is proposed. First, double-vector observations were derived. Then the initial attitude for the guided projectiles was estimated by the regressive quaternion estimation (QUEST) algorithm. Further, the estimated errors were analyzed, and the reason for using the changing acceleration for the in-flight alignment was explained. A simulation and semi-physical experiment was performed to show the effectiveness of the proposed method. The results showed that the initial attitude error for the rolling angle was about 0.35°, the pitch angle was about 0.1° and the heading angle was about 0.6°, in which the initial shooting angle was between 15° and 55°. In future studies, the field experiments will be carried out to test the stability of the proposed in-flight alignment for guided projectiles.

show abstract

Motion Constraints and Vanishing Point Aided Land Vehicle Navigation

Cited by 19 publications

References 38 publications

Optical and Mass Flow Sensors for Aiding Vehicle Navigation in GNSS Denied Environment

Optical and Mass Flow Sensors for Aiding Vehicle Navigation in GNSS Denied Environment

A Novel Fault-Tolerant Navigation and Positioning Method with Stereo-Camera/Micro Electro Mechanical Systems Inertial Measurement Unit (MEMS-IMU) in Hostile Environment

Research on In-Flight Alignment for Micro Inertial Navigation System Based on Changing Acceleration using Exponential Function

Contact Info

Product

Resources

About