Abstract: This paper proposes a method for combining stereo visual odometry, Light Detection And Ranging (LiDAR) odometry and reduced Inertial Measurement Unit (IMU) including two horizontal accelerometers and one vertical gyro. The proposed method starts with stereo visual odometry to estimate six Degree of Freedom (DoF) ego motion to register the point clouds from previous epoch to the curren...

The determination of image orientation parameters of any sensor during data acquisition became possible by combined use of an inertial measurement system (IMU) and GPS. In this integrated system, GPS antenna, IMU and imaging sensor are located different position in airborne carrier. Because of this reason, the displacement vectors between sensors have to be determined. Similarly, axes of the IM...

In this paper, authors proposed a practical motion estimation strategy to obtain the single static object position and the vehicle’s motion parameters simultaneously by utilizing camera and IMU (Inertial Measurement Unit), and tried several classic nonlinear parameters estimation methods on this problem based on the Matlab simulation. A lot of preliminary calibration experiments have been done ...

Micro-electro-mechanical-systems (MEMS) inertial measurement unit (IMU) outputs are corrupted by significant sensor errors. The navigation errors of a MEMS-based inertial navigation system will therefore accumulate very quickly over time. This requires aiding from other sensors such as Global Navigation Satellite Systems (GNSS). However, it will still remain a significant challenge in the prese...

PURPOSE to use complementary cine EPID and gimbals log file analysis for in-vivo tracking accuracy monitoring. METHODS A clinical prototype of dynamic tracking (DT) was installed on the Vero SBRT system. This prototype version allowed tumor tracking by gimballed linac rotations using an internal-external correspondence model. The DT prototype software allowed the detailed logging of all appli...

Visual and inertial sensors, in combination, are able to provide accurate motion estimates and are well-suited for use in many robot navigation tasks. However, correct data fusion, and hence overall performance, depends on careful calibration of the rigid body transform between the sensors. Obtaining this calibration information is typically difficult and time-consuming, and normally requires a...

Navigation in autonomous vehicles involves integrating measurements from on–board inertial sensors and external data collected by various sensors. In this paper, the computer–frame velocity error model is augmented with a random constant model of accelerometer bias and rategyro drift for use in a Kalman filter–based fusion of a lowcost rotating inertial navigation system (INS) with external pos...

The time delay calibration between Light Detection and Ranging (LiDAR) and Inertial Measurement Units (IMUs) is an essential prerequisite for its applications. However, the correspondences between LiDAR and IMU measurements are usually unknown, and thus cannot be computed directly for the time delay calibration. In order to solve the problem of LiDAR-IMU time delay calibration, this paper prese...

OBJECTIVE To evaluate the use of inertial measurement units (IMU) for quantification of canine limb kinematics. METHODS Sixteen clinically healthy, medium-sized dogs were enrolled. Baseline kinematic data were acquired using an optical motion capture system. Following this baseline data acquisition, a harness system was used for attachment of IMU to the animals. Optical kinematic data of dogs...