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6

Yes. The px4 software for the pixhawk autopilot has an extended kalman filter that uses an accelerometer, a gyroscope, gps, and mag. A paper describing the a smaller ekf which only estimates attitude can be found on archive.org and code for the full ekf can be found on github with further information on archive.org.


5

In my opinion, the main difference is : Positioning : gives information about the robot coordinates. It gives raw data that you can use. Localization : it is the process of the robot (or other actor) locating itself (or the robot) on the map. Here a "method is applied" to locate the robot. Positioning gives you the coordinates. Localization is determining ...


5

A Vicon motion capture system system is used in the TED Talk that you referenced. It is similar to a Kinect in that gives the 3D coordinates of any object being tracked within its field of view. Like the Kinect it uses IR, but uses IR reflective balls attached to the quadrotor and the presenters pointer to identify and track objects. Not to mention it is a ...


4

I know this is an old question but I will just add a bit to the currently existing answers. First, this is a very complex problem that everyone is trying to tackle, including google with their Tango project. In general, to localise indoor you either need to rely on your internal sensors, or get assistances from a indoor infrastructure deployed to assist you ...


4

I would go with one of two-ish methods to do this, but both methods require the craft to know its own position. You could do this with GPS, or an IMU, or any other means or combination of position tracking. Method 1 - Only track where you are and where "home" is. Use sensors to detect obstacles along your path and navigate around them as applicable. ...


4

Precise vehicle location is not a very useful piece of data in autonomous driving so I would not expect to see many products focusing on it. Path planning and following for cars is a solved problem. If you have a static environment where nothing changes, any good position sensing will let you control a vehicle to follow a path. However, there are very few ...


4

You can use a very low information matrix value at the orientation elements of your state, given that the information matrix is the inverse of the covariance matrix. The covariance matrix represents the uncertainty about the measurement, and the information matrix the certainty about it. So, the GPS constraints would have a small value at the elements ...


4

This is a complete re-working of the answer I had originally provided. If you're curious, you can check the edit history and see what was posted earlier. In comments to this question, OP stated that they might be able to get throttle and steering angles for the robot, but they probably wouldn't be accurate. That's okay; it's better than nothing. OP also ...


3

ROS has a package called robot_localization that can be used to fuse IMU and GPS data. This package implements Extended and Unscented Kalman filter algorithms. The package can be found here.


3

The NS-HP is a $50 RTK-capable GPS receiver providing centimeter-level accuracy: NS-HP is a high performance GPS receiver capable of 2 / 4 / 5 / 8 / 10 / 20 / 25 / 40 / 50 Hz update rate. At 1Hz update rate, NS-HP can accept RTCM 3.x message type 1002, 1004, 1005, and 1006, or SkyTraq raw measurement data from a base station to perform carrier phase RTK ...


3

There is an error in your posted equation for the Jacobian $F_J$, so that could be the source of the problem. It should look like this: $F_J = \begin{bmatrix} 1 & 0 & -C \sin \theta \\ C \frac{\sin \theta \sin \lambda}{\cos^2 \lambda} & 1 & C \frac{\cos \theta}{\cos \lambda} \\ 0 & 0 & 1 \\ \end{bmatrix}$ With that new Jacobian I ...


3

I work on race cars which occasionally race in built up areas such as street circuits. As part of the mandatory electronic systems we fit a GPS antenna to the car to allow vehicle tracking. Some of the guidance we have for the installation is Fit the antenna to the upper surface of the car Keep the antenna within 5 degrees of horizontal Do not place ...


3

I actually work as a programmer for the tractors that bit-pirate mentioned. There are several ways mentioned that can get you more accurate results. It depends largely on your application and what you are trying to accomplish. WASS uses a signal to augment not as accurate as some other methods but you will get decent. If your platform is fixed you can just ...


3

No, it is not possible to eliminate the cumulative position error caused by sensor noise and bias without using an additional sensor which can report any kind of position measurement. Even the best sensors and filtering will not be able to eliminate in a closed-loop fashion the position error.


3

Do you have a simulation? I would recommend that you simulate the data first to debug and tune your KF. The simulation should model the true IMU outputs (Grove has some details on that) and true position with error models. Start with truth to make sure the KF estimates zero errors, and then add errors one at a time (bias, SF, Misalignment, noise, etc.) to ...


2

Optical flow sensors (such as those used in computer mouses) are good for this situation. Most will give output in terms of translation. Alternatively, you can just use a basic camera and run some optical flow algorithms on the data. This will give you the same basic information. It might be easier when doing it this way, to adapt an algorithm that will ...


2

Yes, it works fine in a plastic (or wood) case. I've used the PA6H GPS from Adafruit in a Hammond 1553B plastic case with no issues. Mostly what you want to avoid is any sort of conductor that might block a signal. This includes copper and iron.


2

The short answer is no. By amplifying a GPS signal, you are creating a multipath situation. Instead of the proper signal path from the satellite directly to the receiver, you would be creating a triangle inequality (unless your amplifiers just happened to be exactly in line between each satellite and the receiver). You might decide that having an imperfect ...


2

GPS relies on trilateration to work. That is, the calculated distance from at least three satellites, to fix. So, for working exactly like in an outdoor GPS covered signal environment I doubt it will be feasible. What you get with that repeaters, is that the indoor devices will get the position of the external antenna/receiver.¹. So if you have a big space ...


2

Depending on your actual project, you can choose several options. DGPS accurate to 0.5 to 2 meters for real time application, meaning get corrected position now. Needs one GPS receiver and one data stream receiver, wireless broadcast and internet/cellularphone, feeding real time correction data (from reference station) to the GPS receiver. RTK is real time....


2

You are already mentioning that RTKLIB and a raw sensor would be the solution. Looking at the list of supported protocols in rtklib, there is a mention of the ublox modules. The LEA6T modules seem to fit and are not very expensive. There is also a simple break out board available which should fit your requirements of not creating hardware.


2

In regards to your question about differential drive, it sounds as though your robot is using the kinematic model to estimate the position, but this is being done "internally" (i.e., in the embedded on-board software). Whether or not this is okay depends on whether the wheel radii and track width (distance between left and right wheels) it uses are correct. ...


2

Ublox sell an RTK solution which provides 2cm accuracy. The evaluation kit is €359 and it works beautifully.


2

Reach RTK (USD$570) looks really good as it is, but what looks promising is that there is an IMU on board, which when integrated should enable less than 1cm error (std. dev.) once the INS has converged. You should also consider that, because you are post-processing your data, to use a cheap GPS and simply smooth the data using an exponential moving average ...


2

I was in exactly the same boat with my master's thesis; wave-based imaging (sonar and radar) seemed so common that all the papers I read assumed you knew the fundamental concept and they were going to show an advanced technique, or they set out deriving everything from Maxwell's equations! That said, I hope this helps. Essentially, you have two ...


2

There are many GPS+INS fusion units available on the market. The price, weight and size of the units can vary dramatically depending on the GPS positioning accuracy and rate of drift from the INS. The choice of GPS+INS sensor really depends on the requirements of your application. From my own experience, Xsens (https://www.xsens.com) make lightweight ...


2

Primarily it will be GPS based. I have a Phantom 3 Pro and I have seen how the Go Home feature works. Before it returns to the x,y coordinates set as "home" it goes to a specific altitude. Presumably this is determined from the altitude of it's home position plus some pre-determined safety zone that is known to be clear of some of the tallest standard ...


2

Of course, it is possible. You need to go for a sensor fusion algorithm, that could be Kalman Filter or Complementary Filter. I personally found very useful the procedure described at the following link, in order to have a total 3D estimation, without suffering any gimbal lock or other problems. EDIT: I am reading only now that you're asking for position ...


2

The answer to this question greatly depends on your acceptable error, and budget. As the other two answers have stated, it is practically impossible to dead-reckon the position without directly observing the position with another sensor; this is however based on assumptions about your acceptable error and IMU selection. If your acceptable error is large ...


2

I have used both KVH CNS-5000 and the Xsens MTi-G-710 that do what you are asking. Both these products provide on-board sensor fusion. The CNS-5000 uses an EKF and I am not sure about the Xsens. They both cost in excess of $4k. I am unaware of any less costly solutions that integrate both the GNSS and IMU.


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