An innovative information fusion method with adaptive Kalman filter for integrated INS/GPS navigation of autonomous vehicles

Mobility is a significant robotic task. It is the most important function when robotics is applied to domains such as autonomous cars, home service robots, and autonomous underwater vehicles. Despite extensive research on this topic, robots still suffer from difficulties when moving in complex environments, especially in practical applications. Therefore, the ability to have enough intelligence while moving is a key issue for the success of robots. Researchers have proposed a variety of methods and algorithms, including navigation and tracking. To help readers swiftly understand the recent advances in methodology and algorithms for robot movement, we present this survey, which provides a detailed review of the existing methods of navigation and tracking. In particular, this survey features a relation-based architecture that enables readers to easily grasp the key points of mobile intelligence. We first outline the key problems in robot systems and point out the relationship among robotics, navigation, and tracking. We then illustrate navigation using different sensors and the fusion methods and detail the state estimation and tracking models for target maneuvering. Finally, we address several issues of deep learning as well as the mobile intelligence of robots as suggested future research topics. The contributions of this survey are threefold. First, we review the literature of navigation according to the applied sensors and fusion method. Second, we detail the models for target maneuvering and the existing tracking based on estimation, such as the Kalman filter and its series developed form, according to their model-construction mechanisms: linear, nonlinear, and non-Gaussian white noise. Third, we illustrate the artificial intelligence approach-especially deep learning methods-and discuss its combination with the estimation method.

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“…Sensors [18,49,50] GPS, IMU [19,51,52] Camera, IMU [36,53] Wi-Fi, IMU [54] GPS, Digital Compass, IMU [37,55,56] UWB, IMU [57,58] RFID, IMU…”

Section: Referencementioning

confidence: 99%

State-of-the-Art Mobile Intelligence: Enabling Robots to Move Like Humans by Estimating Mobility with Artificial Intelligence

Kong

Bai

et al. 2018

Applied Sciences

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“…Kalman filter is a popular filter used to eliminate the GPS noises [75], moreover, a moving average filter is a simplified filter to extract the semi-static movement of structures [3]. Also, an adaptive filter is applied alone or integrated with Kalman filter to denoise the GPS measurements for structures [76]. Additionally, a high-pass and a low-pass Type I Chebyshev filter are used to estimate the behavior of structures based on GPS measurements [3,49].…”

Section: Recent Dynamic Behavior Assessment Of Structuresmentioning

confidence: 99%

Recent Advances of Structures Monitoring and Evaluation Using GPS-Time Series Monitoring Systems: A Review

Kaloop

Elbeltagi

et al. 2017

IJGI

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This paper presents the recent development in Structural Health Monitoring (SHM) applications for monitoring the dynamic behavior of structures using the Global Positioning Systems (GPS) technique. GPS monitoring systems for real-time kinematic (RTK), precise point positioning (PPP) and the sampling frequency development of GPS measurements are summarized for time series analysis. Recent proposed time series GPS monitoring systems, errors sources and mitigation, as well as system analysis and identification, are presented and discussed.

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“…However, the positioning accuracy is low in the case of the GPS signal anomaly. Liu et al [10] presented a method which could effectively improve the inertial navigation system (INS)/GPS measurement accuracy by continuously updating the noise variance and collecting the estimates and measurements to deal with the noise variance of the system. The noise changes due to environmental disturbances could be treated by introducing attenuation factors and increasing the weight of current values.…”

Section: State Of the Artmentioning

confidence: 99%

Instantaneous Datum Reconstruction Method of Multi-Beam Transducer in Short- Time GPS Signal Anomaly

Wang¹,

Wang²,

Wu³

et al. 2017

JESTR

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The short-time signal anomaly of Global Positioning System (GPS) often occurs in the process of multi-beam bathymetry, which leads to the poor accuracy of multi-beam acoustic emission of instantaneous position datum and affects the underwater topographic survey accuracy to a large extent. This study proposes a novel method to reconstruct multi-beam transducer instantaneous datum in the event of the short-time GPS signal anomaly to solve this problem. First, the synchronization of GPS and inertial measurement unit (IMU) was realized by establishing the correlation coefficient model. Second, the fast Fourier transformation filter was used to extract the long-period signal from the GPS elevation signal, which was repaired according to the Heave sequence, and the instantaneous elevation datum was reconstructed through attitude correction. Finally, the original plane information was obtained through Kalman filtering. The error accumulation of the original plane information was eliminated by using the fixed solution which had returned to normal, and then the instantaneous plane datum was reconstructed. The reliability of this method was proven through simulation experiments. Results demonstrate that the similarity between the GPS elevation sequence and Heave sequence can synchronize GPS and IMU. In addition, the instantaneous datum accuracy of the multi-beam transducer reconstructed through this method can reach the necessary cm-level to satisfy the requirements for the positioning accuracy in open water. The proposed method can establish a highly precise basis of data for the underwater seabed topographic monitor of signal anomaly areas in quayside and sea-crossing bridges.

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An innovative information fusion method with adaptive Kalman filter for integrated INS/GPS navigation of autonomous vehicles

Cited by 240 publications

References 28 publications

State-of-the-Art Mobile Intelligence: Enabling Robots to Move Like Humans by Estimating Mobility with Artificial Intelligence

State-of-the-Art Mobile Intelligence: Enabling Robots to Move Like Humans by Estimating Mobility with Artificial Intelligence

Recent Advances of Structures Monitoring and Evaluation Using GPS-Time Series Monitoring Systems: A Review

Instantaneous Datum Reconstruction Method of Multi-Beam Transducer in Short- Time GPS Signal Anomaly

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