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7

I still think this is off-topic, but it seems I need more space than a comment to show (answer?) why that is so. You are starting from some performance specifications and are looking to get to a set of features you need in your camera. Here is a post from NI about stereo vision that gives a formula for depth resolution: $$ \Delta z = \frac{z^2}{fb}\...


7

You can use the Jacobians of the inverse observation model to initialize the new row/column of the covariance matrix. Suppose your observation model is $g(\mathbf{x})$, which maps your state $\mathbf{x}$ to a predicted observation $\hat{\mathbf{z}}$. The inverse observation model $g^{-1}(\mathbf{x}, \tilde{\mathbf{z}})$ maps an observation $\tilde{\mathbf{...


6

Hi and welcome to the wide, ambiguous, sometimes confusing world of research. But seriously, looking at 20 years of papers will sometimes produce these confusions. Let's look at what's going on. In the first reference, what they are saying is: An INS/Gyro is nice, but has an error in it. That error changes (drifts) over time. Therefore, the error in the ...


4

OK. I'm too lazy to read the document, but in general you can model the sensor response as $$\alpha_m = S \alpha + b$$ where $\alpha$ is the actual acceleration in three dimensions with respect to the accelerometer body (including the acceleration due to gravity), $\alpha_m$ is the measured acceleration from the accelerometer, $b$ is an offset, and $S$ is ...


3

The interpretation of error for a robot manipulator pose is subjective in terms of what is the error being used for. A robot manipulator pose is combination of both position (x, y, z) and the orientation (quaternions or euler angles) and thus, designing the error could partially or completely include all terms. Your representation of error is essentially ...


3

I realize this question is 2 years old, but I have direct recent experience with this. The way I did this is with 6 rotated cube positions with 1000 points at each position, so a total of 6000 samples. I'm assuming Matlab/numpy nomenclature, where NxM means N rows and M columns. I assume an equation like Ax = B where B is the measured values matrix (...


2

Ian's answer is mathematically correct. However, on most processors division takes longer than multiplication. So if you're at all pressed for processor resources you would want to precalculate a gain and offset for each channel, and apply it: $k_{zz} = \frac{1}{S_{zz}}$ $b_{zz} = -\frac{B_z^{0g}}{S_{zz}}$ $a_{z1}^{corrected} = k_{zz} a_{z1} + b_{zz}$


2

As noted at the top of the second page: $B_z^{0g} = a_{z1}-S_{zz}*1g$ The "ground truth" z-axis acceleration (of an accelerometer sitting flat on the table) is $1g$, which is affected by the sensitivity of the accelerometer along that axis. You could rewrite it as follows: $$Bias = a_{measured} - Sensitivity * a_{actual}$$ Since you want to calculate ...


2

For very high-precision applications such as finishing, milling by CNC machines, jerk-bounded trajectories (that is, trajectories comprising polynomials of degree 3 of higher) are often used. If you search on Google Scholar using the term "jerk bounded", you can find loads of methods to plan such trajectories. High-order polynomial trajectories (or splines) ...


2

Basically, the relative magnitude between process and measurement noise determines how much to trust a new sensor measurement. In one extreme, if the process noise is zero the kalman filter will effectively ignore new sensor measurements because you've told it the process model is perfect (i.e. zero noise). At the other extreme, if you set the process ...


2

I'll try to explain this in terms of software. Firstly, it is just next to impossible to have 100 metres (practically, 3 metres is like the best depth accuracy) and we need to be sure that the cameras are capturing images properly with all practical features (vibration-free and even under sunlight or rain)! (Else features will be lost and we end up with ...


1

As I understand your workspace send to the /odom topic geometry_msgs/PoseArray and you are trying to read it as nav_msgs/Odometry, As you can see they have totally different struct. I can imagine that you don't want to change the "The Construct" code, so my suggestion would be to create an intermediate topic in order to "translate" the poseArray to Odometry. ...


1

When the manipulator's tool position $p_\text{tool} = (x_\text{tool}, y_\text{tool}, z_\text{tool})$ is different from the point $p_\text{target} = (x_\text{target}, y_\text{target}, z_\text{target})$ where the manipulator should go to, we say there is position error. Intuitively, position error $e$ should tell us how far the current tool point $p_\text{...


1

It's a little difficult to visualize rotations of a rotation sensor, so let's consider an accelerometer instead. You've got the same problem with an accelerometer: if the sensor isn't aligned with the chassis frame, you introduce a relative rotation $R_{struct}$. Now, let's suppose some properties to go along with the accelerometer. We'll say it measures x-...


1

Robots use many coordinate system and for each position you transmit to the robot, it has to be specified in which coordinate system is it defined. If you do not define it explicitly, an implicit definition is used, which may not correspont to the one in which the current postition is defined. So what you think is exaclty near the robot, may be actually out ...


1

Ostensibly, the error in angular and linear velocity of the Create 2 is quite large--this is due in part to limitations of open-loop control of the robot based on motor encoders that introduce significant inaccuracy to the system. You can find many similar questions addressing this same concern.


1

Yes, you have an issue, and it has to do with the parameterization of rotations. As you have it, your $e_{ij}$ will be a $7\times 1$ column, but your pose has only six degrees of freedom (three for translation, three for rotation). There is actually a constraint that isn't properly represented in your optimization function (the norm of a unit quaternion must ...


1

I don't have experience with SLAM specifically, but I do have a lot of EKF experience so here's my input. Stick with your second approach. It is normal for the error to approach a non-zero steady-state value. This number can be calculated analytically for nominal cases, but I don't remember the math right now and would probably be too complicated anyhow ...


1

I've got two Universal Robots guys in the room with me here, so I asked them this question. When the robot's performing a Trajectory move (e.g. linear move) then the dynamic precision is the same as the static precision (±0.1mm). The robot would need to be set up correctly, and know the weight of its payload, so it can correctly balance itself. When the ...


1

Have you tried turning on either the "Backface Culling" or the "Polygon Transparency Sorting" settings under Shading? Those settings affect the rendering of polygons based on view distance and can potentially speed up the rendering process as well as hide incorrectly drawn surfaces.


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