Questions tagged [sensor-fusion]

Sensor fusion is a process by which data from several different sensors are "fused" to compute something more than could be determined by any one sensor alone.

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Angle Random Walk vs. Rate Noise Density (MPU6050)

I’ve made a datalog from a MPU6050 (IMU: gyroscope and accelerometer) at 500Hz sample rate. Now I want to calculate the characteristics from the gyro to evaluate the sensor. For the gyro I’ve found ...
4
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1answer
298 views

Yaw drift when implementing AHRS filter fusion

I am using the Matlab AHRS filter fusion algorithm with an InvenSense ICM-20948 to determine object orientation. I seem to be obtaining reasonable results however I am getting what appears to be ...
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0answers
436 views

How does one implement a third order complementary filter for estimating altitude using data from an accelerometer and a barometer?

I am working with the CJMCU build of cleanflight on a small drone. As of now, the algorithm for altitude hold uses a first order complementary filter to combine data from the barometer and the ...
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50 views

Kalman Filter for 2d pose

I'm really sorry if this is a dumb question, but I don't have a clue on how to do this. I'm trying to write a kalman filter with a State vector of : {x, y, ẋ, ẏ, ẍ, ÿ } To estimate the 2 dimensional ...
2
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1answer
56 views

Is it possible to track position using gyroscope and accelerometer without a magnetometer?

I'm looking for help on a project where I will be placing sensor data in 3D space using augmented reality. Most solutions I have found for finding position with an IMU involve the magnetometer, but ...
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0answers
115 views

How to handle sensor data for a sensor-fusion algorithm

I am implementing the explicit complementary filter(see below) with a 9DOF MEMS sensors (accelerometer, magnetometer and gyroscope) for attitude estimation. Currently, the gyro and accel update rates ...
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0answers
101 views

Position-Attitude Kalman filter with Quaternions

I want to design an EKF to estimate the position of a UAV. If I were doing this with Euler angles then I would have a state vector that would look like \begin{bmatrix}north&east&down&...
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0answers
588 views

Correcting GPS track with visual odometry (sensor fusion)

I am trying to build low cost and precise outdoor positioning. I explored NS-RAW with RTKLIB - this would be doable but probably will need either a base station to get the correction data for rover or ...
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2answers
65 views

Sensor fusion of GNSS and IMU using UKF

I do have a land-based robot with an IMU and a GNSS receiver. From the IMU, I get the velocity and acceleration in both $x$ and $y$ directions. From the GNSS receiver, I get the latitude and ...
1
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1answer
137 views

How to synchronise data for fusion in Kalman from multiple sensors with different timestamp information?

I'm using Kalman filter to track the position of a vehicle and receive position data from 2 sensors: A GPS sensor and an Ultrasonic sensor for which I want to implement sensor fusion into the Kalman. ...
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0answers
50 views

Sensorfusion of odometry, accelerometer and gyroscope using Indirect Kalman Filter

I'm trying to implement an indirect Kalman for pose estimation of a wheeled robot. I found two papers that describe this approach. CMU. Journal (2006) Vol. 5(1) IFAC Conference on Embedded Systems ...
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0answers
55 views

Kalman filter to fuse ultrasonic altitude sensor and accelerometer

I'm a little confused on how to set up the Kalman filter matrices to fuse an ultrasonic altitude sensor and accelerometer from IMU. I am trying to implement this for a quadcopter. And what I'm ...
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1answer
212 views

Position Estimates from sensor fusion

I have a quadcopter, and several components in play. First, I have a real position system (VICON), and I also have a SLAM platform. Then, of course, the IMU on the quadcoptor. I am trying to ...
1
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1answer
89 views

Sensor fusion with gyroscope and motor rotations

I am building a robot (2 powered wheels and one ball bearing). The problem is that I can't seem to make it drive straight. I literally find it impossible, I have been trying for weeks. I have two ...
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144 views

Kalman filter for slow ground vehicle with RTK

I have been using dual RTK receivers for my tractor projects. This gives me reliable position, heading, and tilt at low rates (10 Hz). I recently began working with an INS (an Advanced Navigation ...
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0answers
488 views

Fusion of GNSS position data and prefused 9-dof AHRS data

Bosch, FreeScale, InvenSense, ST and maybe others are releasing 9-dof AHRS platforms containing their own fusion software and outputting filtered/sane/fused data (attitude as quaternion and linear ...
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8 views

ECEF postion vs. LAT/LON/Height position with odometry

So I do have a wheeled robot and I want to fuse position data with odometry data. Someone suggested using the position encoded in ECEF rather than using the LAT/LON/Height information I get from the ...
0
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1answer
30 views

Bias correction for multiple sensor fusion through Kalman Filtering

I am learning Kalman Filters and was working on a simple example: Temperature measurement of a room by using 4 thermometers(different biases and noises) if i consider that there is no bias in the ...
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0answers
14 views

Relative pose of 2 sensors in rigid body

I have a robot (gray box in the picture) that I can rotate in 3D (x, y, z) relative to a center of rotation. Let's say that this robot has two sensors with fixed poses in the robot: One IMU that can ...
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21 views

get position of objects using ir

I originally wanted to make a shoddy vr system with two IMU's in two seperate right and left controllers, which their values could be sent over wifi to the game service unity so I can plot their ...
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0answers
12 views

Simulation flight gives inconsistent sensor data

I made a short outdoors flight of 10 minutes with hector quadrotor on Ubuntu 16.04 Gazebo 7. The sensor readings and the path images are as attached. The flight was simple. I took of slowly, moved ...
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26 views

Algorithms for IMU sensors calibration in real time on arduino due?

Im working on a 10 DOF IMU system for quadcopter project. I understand the need for sensor calibration but uptil now I have seen offline ways to compute the calibration offsets/biases, where we take a ...
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31 views

How to obtain airspeed data

I want to measure the airspeed on a flying vehicle and get the data with a microcontroller. Note that, there will not be any control mechanism on the flying object, it will be flying mechanicaly/...
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1answer
54 views

SLAM techniques based on contact, odometry and one front camera

Consider a mobile robot provided with a contact sensor that randomly travels in a closed environment, changing direction every time an obstacle is encountered. Is it possible to reconstruct the 2D map ...
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2answers
287 views

Convert Vehicle coordinates to World coordinates for positioning

I'm tracking the position of a vehicle along a certain trajectory using the Kalman filter and the idea is to check for improvements in position estimation through fusion of data from multiple sensors (...
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43 views

Can a RPI3B+ handle all this?

I am building a robot that needs to accomplish the following tasks: Keep track of 4 quadrotor encoders, each 979.62 CPR @ ~ 500RPM, so ~ 8163.5 counts per second Read from an RPlidar A1M8, giving out ...
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1answer
153 views

How to do IMU and camera “sensor fusion” tracking?

I have some 50ms latency cameras at hand and a 800Hz IMU (gyro+accelerometer+magnetometer). I would like to know how exactly how I should do a sensor fusion of such an IMU and camera to fix the ...
0
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1answer
309 views

How to model transition matrix in indirect kalman filter with external orientation estimate

I am trying to implement an indirect/error state kalman filter following Quaternion kinematics for the error-state Kalman filter. However, instead of modelling the orientation and error in orientation ...
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2answers
170 views

Sensor fusion to calculate joint angles between segments of a robot arm using IMU data

I have an IMU attached to each of the segments of a robotic arm, which gives me accelerometer and gyroscope data. My goal is to first of all improve the quality of the sensor readings and subsequently ...