Multiple ultrasonic aiding system for car navigation in GNSS denied environment

Moussa, Mohamed; Moussa, Adel; El‐Sheimy, Naser

doi:10.1109/plans.2018.8373374

Cited by 6 publications

(6 citation statements)

References 28 publications

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“…However, if these APs are affected in a similar manner, the effect on the position estimates could be negligible [75,76]. Although, this survey paper has focused on Wi-Fi, GNSS updates can be fused with other complimentary location sensors [77][78][79][80]. Moreover, multiple wireless ranging techniques discussed can be combined as shown in [81].…”

Section: Resultsmentioning

confidence: 99%

Infrastructure Wi-Fi for connected autonomous vehicle positioning: A review of the state-of-the-art

Adegoke

Zidane

Kampert

et al. 2019

Vehicular Communications

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Section: Resultsmentioning

confidence: 99%

Infrastructure Wi-Fi for connected autonomous vehicle positioning: A review of the state-of-the-art

Adegoke

Zidane

Kampert

et al. 2019

Vehicular Communications

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“…The ultrasonic sensors are used for detecting walls and keeping a constant range from these walls while it navigates. (Moussa et al, 2018) used multiple ultrasonic system as an aiding sensor to the INS during GNSS signal outage through providing velocity updates. This system was mounted facing the left and right rear wheels to estimate the angular velocity of the rotating wheels through sensing the ranges between the ultrasonic sensor and the spokes of the wheels.…”

Section: Related Workmentioning

confidence: 99%

“…The proposed integration scheme between ultrasonic aiding system and INS is described in Figure 18. The ultrasonic aiding system consists of a front ultrasonic sensor to estimate the change of heading as described before and an ultrasonic odometer to provide the filter with velocity updates as described in (Moussa et al 2018). The ultrasonic aiding system integrates with the INS to mitigate its large drift to provide an enhanced integrated navigation solution.…”

Section: Integration Schemementioning

confidence: 99%

Ultrasonic Based Heading Estimation for Aiding Land Vehicle Navigation in GNSS Denied Environment

Moussa

El‐Sheimy

2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. This paper introduces a novel approach for land vehicles navigation in GNSS denied environment by aiding the Inertial Navigation System (INS) with a very low-cost ultrasonic sensor using Extended Kalman Filter (EKF) to bound its drift during GNSS blockage through a heading change update to enhance the navigation estimation.The ultrasonic sensor is mounted on the body of the car facing the direction of the car motion and behind the front right wheel, a wooden surface is mounted on the car body on the other side of this wheel with a constant distance between the sensor and this surface. The ultrasonic sensor measures this range as long as the car moving straight. When orientation changes, the ultrasonic sensor senses the range to the front right wheel. The relation between the range and the estimated GNSS/INS change of heading during GNSS availability is estimated through a linear regression model. During GNSS signal outage, the ultrasonic sensor provides heading change update to the INS standalone navigation solution.Experimental road tests were performed, and the results show that the navigation states estimation using the proposed aiding is improved compared with INS standalone navigation solution during GNSS signal outage. For multiple GNSS outages of 60seconds, the inclusion of the proposed update reduced the position RMSE to around 80% of its value when using the non-holonomic constraints and velocity update only.

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“…It is essential to extract this data accurately because the movement of the robotic agent depends on this data as seen in [1], where three robots map a labyrinth together in order to solve it. Most of the algorithms developed today are based on a system of integrated sensors, such as for example ultrasonic [2] or laser as is the case of [3]. At the national level, some examples of these situations can be seen [4][5], which generates a series of limitations when dealing with certain situations, such as distinguishing between two different types of objects.…”

Section: Introductionmentioning

confidence: 99%

Robotic navigation algorithm with machine vision

Pachón¹,

Enciso-Aragon²,

Moreno³

2020

IJECE

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In the field of robotics, it is essential to know the work area in which the agent is going to develop, for that reason, different methods of mapping and spatial location have been developed for different applications. In this article, a machine vision algorithm is proposed, which is responsible for identifying objects of interest within a work area and determining the polar coordinates to which they are related to the observer, applicable either with a fixed camera or in a mobile agent such as the one presented in this document. The developed algorithm was evaluated in two situations, determining the position of six objects in total around the mobile agent. These results were compared with the real position of each of the objects, reaching a high level of accuracy with an average error of 1.3271% in the distance and 2.8998% in the angle.

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Multiple ultrasonic aiding system for car navigation in GNSS denied environment

Cited by 6 publications

References 28 publications

Infrastructure Wi-Fi for connected autonomous vehicle positioning: A review of the state-of-the-art

Infrastructure Wi-Fi for connected autonomous vehicle positioning: A review of the state-of-the-art

Ultrasonic Based Heading Estimation for Aiding Land Vehicle Navigation in GNSS Denied Environment

Robotic navigation algorithm with machine vision

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