scholarly journals Trends in Inertial Navigation Technologies

2021 ◽  
Vol 906 (1) ◽  
pp. 012069
Author(s):  
Stanislav Hodas ◽  
Jana Izvoltova ◽  
Donatas Rekus
Keyword(s):  
Real Time ◽  
Inertial Measurement Unit ◽  
Electronic Device ◽  
Inertial Navigation ◽  
Relative Orientation ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Below Ground ◽  
Autonomous Technology

Abstract The inertial measurement unit is an electronic device built-in practically in any controlled or autonomous technology used for land mapping. It is based on a combination of accelerometers and gyroscopes and sometimes magnetometers used for relative orientation and navigation. The paper is focused on functions and trends of an inertial measurement unit, which is a part of inertial navigation indicator of position and velocity of moving devices on the ground, above and below ground in real-time.

scholarly journals Real-Time Gait Analysis Using a Single Head-Worn Inertial Measurement Unit

2018 ◽  
Vol 64 (2) ◽  
pp. 240-248 ◽  
Author(s):  
Tong-Hun Hwang ◽  
Julia Reh ◽  
Alfred O. Effenberg ◽  
Holger Blume
Keyword(s):  
Gait Analysis ◽  
Real Time ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Inertial Measurement

Development and Implementation of a Novel Digital Shot Sensor System

2013 ◽  
Vol 364 ◽  
pp. 228-232
Author(s):  
Wei Tian Wang ◽  
Quan Jun Song ◽  
Yu Man Nie ◽  
Bu Yun Wang ◽  
Hong Yu Ren ◽  
...  
Keyword(s):  
Real Time ◽  
Information Acquisition ◽  
Inertial Measurement Unit ◽  
Degrees Of Freedom ◽  
Sensor System ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Kinetic Information ◽  
Shot Put

Kinetic information acquisition of shot throwing is significant for the train of shot put athletes. This paper presents a novel sensor system based on a 9 degrees of freedom inertial measurement unit, which provides attitude information of shot throwing in real time. The sensor system is designed with modularized structure and installed in the digital shot which has almost the same size and weight as the standard shot for females. A multi-target and multi-parameter information acquisition platform is constructed to acquire kinematics information. With the help of the sensor system, the coaches can combine attitude information with kinematics data to analyze the shot throwing movements.

Global Observability Analysis IMU/Camera Integration

2013 ◽  
Vol 380-384 ◽  
pp. 1069-1072
Author(s):  
Qiang Fang ◽  
Xin Sheng Huang
Keyword(s):  
State Estimation ◽  
Inertial Measurement Unit ◽  
Sufficient Conditions ◽  
Inertial Navigation ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Inertial Measurement ◽  
Observability Analysis ◽  
Inertial Measurements

Vision-aided inertial navigation systems can provide precise state estimates for the 3-D motion of a vehicle. This is achieved by combining inertial measurements from an inertial measurement unit (IMU) with visual observations from a camera. Observability is a key aspect of the state estimation problem of INS/Camera. In most previous research, conservative observability concepts based on Lie derivatives have extensively been used to characterize the estimability properties. In this paper, we present a novel approache to investigate the observability of INS/Camera: global observability. The global observability method directly starts from the basic observability definition. The global observability analysis approach is not only straightforward and comprehensive but also provides us with new insights compared with conventional methods. Some sufficient conditions for the global observability of the system is provided.

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

Robotica ◽  
2012 ◽  
Vol 30 (7) ◽  
pp. 1203-1212 ◽  
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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