I want to place virtual objects (holograms) at far distances (20+ meters) in the HoloLens 1. However, at such distances holograms become unstable and appear to "swim" in the display. Has anyone had success with this? What worked for you?
Some potential fixes include:
Ensure 60 FPS
Adjust Stabilization Plane
Employ visual markers (vuforia)
Use static room scan (may not scale well)
For me, frame rate is not an issue. And I am using Unity 2017.4.4f1. Currently, I have a single world anchor and all objects are set relative to this anchor.
20+ meters is a lot and I am not sure if this will work good enough.
Ensuring 60 fps or at least 50/55+ is important but this wont solve the swimming at this distance. A low framerate might only cause additional swimming :)
Everything that should appear statically placed in the room should be on or very close to the stabilization plane. So what you want to avoid is having the far objects at very different distances from the user. That would otherwise cause the ones farthest off from the stabilization plane to swim.
If you only have the far away object try placing the stabilization plane at the same distance as the object, if the distances are changing a lot you can also update the stabilization plane distance at runtime to always set it to the current distance to the object.
Would be interesting to hear if it worked out :)
One more thing: If I remember correctly, objects should ideally placed directly or in close proximity to their world anchor to help stabilization.
20 metres is too far. The docs
Best practices When holograms cannot be placed at 2m and conflicts
between convergence and accommodation cannot be avoided, the optimal
zone for hologram placement is between 1.25m and 5m. In every case,
designers should structure content to encourage users to interact 1+ m
away (e.g. adjust content size and default placement parameters).
Related
I have this simple domino scene where you can click a domino and apply a force to knock it.
At first I had this dominoes in a scale of (x=0.1), (y=0.6), (z=0.3) 1 is supposed to be 1 meter, they fell without a problem but too slow. According to unity documentation on Rigidbody this made total sense.
Use the right size.
The size of the your GameObject’s mesh is much more important than the mass of the Rigidbody. If you find that your Rigidbody is not behaving exactly how you expect - it moves slowly, floats, or doesn’t collide correctly - consider adjusting the scale of your mesh asset. Unity’s default unit scale is 1 unit = 1 meter, so the scale of your imported mesh is maintained, and applied to physics calculations. For example, a crumbling skyscraper is going to fall apart very differently than a tower made of toy blocks, so objects of different sizes should be modeled to accurate scale.
So I just re sized the dominoes to (x=0.01), (y=0.06), (z=0.03), this time they fell to the desired speed but for some reason they stop falling and don't knock the next domino.
example GIF
I don't know why this is happening but i can guess that this is because at the time of calculating physics the engine doesn't waste so much resources in calculating small objects that are probably not even going to be seen by the user.
Modifying mass doesn't seem to do anything, also draw and angular draw are both 0 and already tried every collision detection mode.
Is there any solution or workaround for this?
In my experience, Unity physics doesn't like too small objects since it introduces rounding errors. A game simulation usually does not need the same accuracy as when you try to land on Mars. Therefore, I usually avoid scales less than 0.1f.
In your case, I would keep the scales at 1.0f and instead experiment with either increasing the world gravitation, changing it from the default -9.81f to -98.1f (Edit - Project Settings - Physics). Or changing the default Time Scale from 1f to 5f (Edit - Project Settings - Time).
Try not to make too big changes in the beginning since it might introduce strange effects on other parts of the gameplay.
Given a set of non-rotated AABB bounds, I'm hoping to create a simpler set of bounds from the original set, that allows for a specified amount of inaccuracy.
Some examples:
I'm working with this in Unity with Bounds, but it's just basic AABB comparison stuff, nothing Unity-specific. I figure someone must have worked out a system for this at some point in the past, but I had no luck searching around. Encapsulating bounds are easy but this is harder, since you can't just iterate through each bounds one by one. Sometimes a simpler solution can only be seen by looking at the whole thing.
Fast performance isn't critical but would be nice. Inaccuracy is OK in both directions (i.e. the bounds may cover a little less than the actual size or a little more). If it helps, I can expect all bounds in the original set to be connected somewhere - no free-floating pieces in a separate group.
I don't expect anyone to write up a whole system to solve this, I'm more hoping that it's already been solved or that maybe there's an obvious process to achieve it that I haven't thought of yet.
This sounds something that could be handled with Surface Area Heuristics (SAH). SAH is commonly used in ray tracing to build better tree like structures were the triangles are stored. There are multiple sources discussing it more. One good is Wald's thesis chapter 7.3.
The basic idea in the SAH built is to start with the whole space and divide it recursively. Division position is decided by sweeping through all reasonable positions and calculating surface area of both child nodes. The reasonable positions are the positions were any triangle has its upper or lower bound. After sweeping through all the candidates, the division with the smallest total surface area in the children is used.
If SAH is not a good idea for your application, you could use similar sweeping through all candidates, but calculate for example the extra space inside the AABBs.
I'm hoping to prototype some very basic physics/statics simulations for "voxel-based" games like Minecraft and Dwarf Fortress, so that the game can detect when a player has constructed a structure that should not be able to stand up on its own.. Obviously this is a very fuzzy definition -- whether a structure is impossible depends upon multitude of material and environmental properties -- but the general idea is to motivate players to build structures that resemble the buildings we see in the real world. I'll describe what I mean in a bit more detail below, but I generally want to know if anyone could suggest either an potential approach to the problem or a resource that I could use.
Here's some examples of buildings that could be impossible if the material was not strong enough.
Here's some example situations. My understanding of this subject is not great but bear with me.
If this structure were to be made of concrete with dimensions of, say, 4m by 200m, it would probably not be able to stand up. Because the center of mass is not over its connection to the ground, I think it would either tip over or crack at the base.
The center of gravity of this arch lies between the columns holding it up, but if it was very big and made of a weak, heavy material, it would crumble under its own weight.
This tower has its center of gravity right over its base, but if it is sufficiently tall then it only takes a bit of force for the wind to topple it over.
Now, I expect that a full-scale real-time simulation of these physics isn't really possible... but there's a lot of ways that I could simplify the simulation. For example:
Tests for physics-defying structures could be infrequently and randomly performed, so a bad building doesn't crumble right as soon as it is built, but as much as a few minutes later.
Minecraft and Dwarf Fortress hardly perform rigid- or soft-body physics. For this reason, any piece of a building that is deemed to be physically impossible can simple "pop" into rubble instead of spawning a bunch of accurate physics props.
Have you considered taking an existing 3d environment physics engine and "rounding off" orientations of objects? In the case of your first object (the L-shaped thing), you could run a simulation of a continuous, non-voxelized object of similar shape behind the scenes and then monitor that object for orientation changes. In a simple case, if the object's representation of the continuous hits the ground, the object in the voxelized gameplay world could move its blocks to the ground.
I don't think there is a feasible way to do this. Minecraft has no notion of physical structure. So you will have to look at each block individually to determine if it should fall (there are other considerations but this is minimum). You would therefore need a way to distinguish between ground and "not ground". This is modeling problem first and foremost, not a programming problem (not even simulation design). I think this question is out of scope for SO.
For instance consider the following model, that may give you an indication of the complexities involved:
each block above height = 0 experiences a "down pull" = P, P may be any of the following:
0 if the box is supported by another box
m*g (where m is its mass which depends on material density * voxel volume) otherwise if it is free
F represents some "friction" or "glue" between vertical faces of boxes, it counteracts P.
This friction should have a threshold beyond which it "breaks" and the block then has a net pull downwards.
if m*g < sum F, box stays where it is. Otherwise, box falls.
F depends on the pairs of materials in contact
for n=2, so you can form a line of blocks between two towers
F is what causes the net pull of a box to be larger than m*g. For instance if you have two blocks a-b-c with c being on d, then a pulls on b, so b should be "heavier" than m*g where it contacts c. If this net is > F, then the pair a-b should fall.
You might be able to simulate the above and get interesting results, but you will find it really challenging to handle the case where there are two towsers with a line of blocks between them: the towers are coupled together by line of blocks, there is no longer a "tip" to the line of blocks. At this stage you might as well get out your physics books to create a system of boxes and springs and come up with equations that you might be able to solve numerically, but in a full 3D system you will have a 3D mesh of springs to navigate iteratively to converge to force values on each box and determine which ones move.
A professor of mine suggested that I look at this paper.
Additionally, I found the keyword for what it is I'm looking for. "Structural Analysis." I bought a textbook and I have a long road ahead of me.
I'm working on an IPhone robot that would be moving around. One of the challenges is estimating distance to objects- I don't want the robot to run into things. I saw some very expensive (~1000$) laser rangefinders, and would like to emulate one using iPhone.
I got one or two camera feeds and two laser pointers. The laser pointers are mounted about 6 inches apart, at an angle The angle of lasers in relation to the cameras is known. The Angle of cameras to each other is known.
The lasers are pointing ahead of cameras, creating 2 dots on a camera feed. Is it possible to estimate the distance to the dots by looking at the distance between the dots in a camera image?
The lasers form a trapezoid from the
/wall \
/ \
/laser mount \
As the laser mount gets closer to the wall, the points should be moving further away from each other.
Is what I'm talking about feasible? Has anyone done something like that?
Would I need one or two cameras for such calculation?
If you just don't want to run into things, rather than have an accurate idea of the distance to them, then you could go "dambusters" on it and just detect when the two points become one - this would be at a known distance from the object.
For calculation, it is probaby cheaper to have four lasers instead, in two pairs, each pair at a different angle, one pair above the other. Then a comparison between the relative differences of the dots would probably let you work out a reasonably accurate distance. Math overflow for that one, though.
In theory, yes, something like this can work. Google "light striping" or "structured light depth measurement" for some good discussions of using this sort of idea on a larger scale.
In practice, your measurements are likely to be crude. There are a number of factors to consider: the camera intrinsic parameters (focal length, etc) and extrinsic parameters will affect how the dots appear in the image frame.
With only two sample points (note that structured light methods use lines, etc), the environment will present difficulties for distance measurement. Surfaces that are directly perpendicular to the floor (and direction of travel) can be handled reasonably well. Slopes and off-angle walls may be detectable, but you will find many situations that will give ambiguous or incorrect distance measures.
I want to ask about jelly physics ( http://www.youtube.com/watch?v=I74rJFB_W1k ), where I can find some good place to start making things like that ? I want to make simulation of cars crash and I want use this jelly physics, but I can't find a lot about them. I don't want use existing physics engine, I want write my own :)
Something like what you see in the video you linked to could be accomplished with a mass-spring system. However, as you vary the number of masses and springs, keeping your spring constants the same, you will get wildly varying results. In short, mass-spring systems are not good approximations of a continuum of matter.
Typically, these sorts of animations are created using what is called the Finite Element Method (FEM). The FEM does converge to a continuum, which is nice. And although it does require a bit more know-how than a mass-spring system, it really isn't too bad. The basic idea, derived from the study of continuum mechanics, can be put this way:
Break the volume of your object up into many small pieces (elements), usually tetrahedra. Let's call the entire collection of these elements the mesh. You'll actually want to make two copies of this mesh. Label one the "rest" mesh, and the other the "world" mesh. I'll tell you why next.
For each tetrahedron in your world mesh, measure how deformed it is relative to its corresponding rest tetrahedron. The measure of how deformed it is is called "strain". This is typically accomplished by first measuring what is known as the deformation gradient (often denoted F). There are several good papers that describe how to do this. Once you have F, one very typical way to define the strain (e) is:
e = 1/2(F^T * F) - I. This is known as Green's strain. It is invariant to rotations, which makes it very convenient.
Using the properties of the material you are trying to simulate (gelatin, rubber, steel, etc.), and using the strain you measured in the step above, derive the "stress" of each tetrahdron.
For each tetrahedron, visit each node (vertex, corner, point (these all mean the same thing)) and average the area-weighted normal vectors (in the rest shape) of the three triangular faces that share that node. Multiply the tetrahedron's stress by that averaged vector, and there's the elastic force acting on that node due to the stress of that tetrahedron. Of course, each node could potentially belong to multiple tetrahedra, so you'll want to be able to sum up these forces.
Integrate! There are easy ways to do this, and hard ways. Either way, you'll want to loop over every node in your world mesh and divide its forces by its mass to determine its acceleration. The easy way to proceed from here is to:
Multiply its acceleration by some small time value dt. This gives you a change in velocity, dv.
Add dv to the node's current velocity to get a new total velocity.
Multiply that velocity by dt to get a change in position, dx.
Add dx to the node's current position to get a new position.
This approach is known as explicit forward Euler integration. You will have to use very small values of dt to get it to work without blowing up, but it is so easy to implement that it works well as a starting point.
Repeat steps 2 through 5 for as long as you want.
I've left out a lot of details and fancy extras, but hopefully you can infer a lot of what I've left out. Here is a link to some instructions I used the first time I did this. The webpage contains some useful pseudocode, as well as links to some relevant material.
http://sealab.cs.utah.edu/Courses/CS6967-F08/Project-2/
The following link is also very useful:
http://sealab.cs.utah.edu/Courses/CS6967-F08/FE-notes.pdf
This is a really fun topic, and I wish you the best of luck! If you get stuck, just drop me a comment.
That rolling jelly cube video was made with Blender, which uses the Bullet physics engine for soft body simulation. The bullet documentation in general is very sparse and for soft body dynamics almost nonexistent. You're best bet would be to read the source code.
Then write your own version ;)
Here is a page with some pretty good tutorials on it. The one you are looking for is probably in the (inverse) Kinematics and Mass & Spring Models sections.
Hint: A jelly can be seen as a 3 dimensional cloth ;-)
Also, try having a look at the search results for spring pressure soft body model - they might get you going in the right direction :-)
See this guy's page Maciej Matyka, topic of soft body
Unfortunately 2d only but might be something to start with is JellyPhysics and JellyCar