Research on Lane a Compensation Method Based on Multi-Sensor Fusion

The curvature of the lane output by the vision sensor caused by shadows, changes in lighting and line breaking jumps over in a period of time, which leads to serious problems for unmanned driving control. It is particularly important to predict or compensate the real lane in real-time during sensor jumps. This paper presents a lane compensation method based on multi-sensor fusion of global positioning system (GPS), inertial measurement unit (IMU) and vision sensors. In order to compensate the lane, the cubic polynomial function of the longitudinal distance is selected as the lane model. In this method, a Kalman filter is used to estimate vehicle velocity and yaw angle by GPS and IMU measurements, and a vehicle kinematics model is established to describe vehicle motion. It uses the geometric relationship between vehicle and relative lane motion at the current moment to solve the coefficient of the lane polynomial at the next moment. The simulation and vehicle test results show that the prediction information can compensate for the failure of the vision sensor, and has good real-time, robustness and accuracy.

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Visual servoing applied to real-time stabilization of a multi-rotor UAV

Robotica ◽

10.1017/s026357471200001x ◽

2012 ◽

Vol 30 (7) ◽

pp. 1203-1212 ◽

Cited By ~ 7

Author(s):

Hugo Romero ◽

Sergio Salazar ◽

Rogelio Lozano

Keyword(s):

Real Time ◽

Inertial Measurement Unit ◽

Visual Servoing ◽

Vision System ◽

Measurement Unit ◽

Translational Velocity ◽

Inertial Measurement ◽

Second Stage ◽

Yaw Angle ◽

Flying Robot

SUMMARYIn this paper we address the problem of stabilization and local positioning of a four-rotor rotorcraft using computer vision. Our approaches to estimate the orientation and position of the rotorcraft combine the measurements from an Inertial Measurement Unit (IMU) and a vision system composed of a single camera. In the first stage, the vision system is used to estimate the position and yaw angle of the rotorcraft, while in the second stage the vision system is used to estimate the translational velocity of the flying robot. In both cases the IMU gives the pitch and roll angles at a higher rate. The technique used to estimate the position of the rotorcraft in the first stage combines the homogeneous transformation approach for the camera calibration process with the plane-based pose method for estimating the position. In the second stage, a navigation system using the optical flow is also developed to estimate the translational velocity of the aircraft. We present real-time experiments of stabilization and location of a four-rotor rotorcraft.

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Design, Development, and Deployment of Real-Time Sensor Fusion (CnW + EKF) for a Linux-Based Embedded System Using Qt-Anywhere

Journal of Sensors ◽

10.1155/2018/8695397 ◽

2018 ◽

Vol 2018 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Felipe P. Vista ◽

Kil To Chong

Keyword(s):

Embedded System ◽

Real Time ◽

Sensor Fusion ◽

Measurement Unit ◽

Design Development ◽

Time Operation ◽

Global Positioning ◽

Real Time Operation ◽

Kalman Filter Algorithm ◽

Electronic Compass

This paper describes the design, development, and implementation of a real-time sensor fusion system that utilizes the classification and weighing plus extended Kalman filter algorithm to derive heading for navigation using inexpensive sensors. This algorithm was previously tested only through postprocessing using MATLAB and is now reprogrammed using Qt and deployed on a Linux-based embedded board for real-time operation. Various data from inexpensive sensors such as global positioning system devices, an electronic compass, and an inertial measurement unit were utilized to ultimately derive a more reliable and accurate heading value. The algorithm flow can be described with the GPS values first being evaluated and classified which are then fused with the EC heading using classification and weighing, whose result is then passed through an EKF to fuse with the IMU data. Real-time tests and trials were done to prove the operational capability of the developed process. The complete setup and configuration processes of the systems for development and deployment via Qt are also provided for those interested to replicate the process.

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Study on Motion Compensation Method for W-band UAV MISAR Real-time Imaging

2020 21st International Radar Symposium (IRS) ◽

10.23919/irs48640.2020.9253940 ◽

2020 ◽

Author(s):

Hui Wang ◽

Zhaoyang Zeng ◽

Man Jiang ◽

Shichao Zheng

Keyword(s):

Real Time ◽

Motion Compensation ◽

Compensation Method ◽

Real Time Imaging ◽

W Band

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Communication infrastructure for situational awareness enhancement in WAMS with optimal PMU placement

Protection and Control of Modern Power Systems ◽

10.1186/s41601-021-00189-9 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Bhargav Appasani ◽

Amitkumar Vidyakant Jha ◽

Sunil Kumar Mishra ◽

Abu Nasar Ghazali

Keyword(s):

Real Time ◽

Situational Awareness ◽

Area Measurement ◽

Measurement Unit ◽

Monitoring And Control ◽

Communication Infrastructure ◽

Wide Area Measurement System ◽

Digital Elevation ◽

Elevation Model ◽

And Control

AbstractReal time monitoring and control of a modern power system has achieved significant development since the incorporation of the phasor measurement unit (PMU). Due to the time-synchronized capabilities, PMU has increased the situational awareness (SA) in a wide area measurement system (WAMS). Operator SA depends on the data pertaining to the real-time health of the grid. This is measured by PMUs and is accessible for data analytics at the data monitoring station referred to as the phasor data concentrator (PDC). Availability of the communication system and communication delay are two of the decisive factors governing the operator SA. This paper presents a pragmatic metric to assess the operator SA and ensure optimal locations for the placement of PMUs, PDC, and the underlying communication infrastructure to increase the efficacy of operator SA. The uses of digital elevation model (DEM) data of the surface topography to determine the optimal locations for the placement of the PMU, and the microwave technology for communicating synchrophasor data is another important contribution carried out in this paper. The practical power grid system of Bihar in India is considered as a case study, and extensive simulation results and analysis are presented for validating the proposed methodology.

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