algorithmic modeling for Rhino
Fatalities are likely to happen in panic situations when people try to evacuate Buildings. In this Video, I will share my experience in using Kangaroo physic...
Would you be willing to share your definition? I have a simple simulation working but keep having problems when setting boundaries for collisions. Very inspiring work.
Other possible brute-force and not elegant solution: compute all springs for every moving agent but change the rest-length and/or stiffness of the springs dynamically using vision cone. If the point of a spring in an obstacle falls inside the cone, then the rest-length and/or stiffness rises...
It's not the best solution but it could work (slowly :P).
I am so glad that I am talking to someone with such an in-depth understanding of geometric modeling! You are right. In fact dividing boundaries to anchor points is not a good choice at all. However, as you have pointed, we cannot dynamically change the anchor-points during the relaxation of the crowd -- i.e. the time span when Kangaroo is running. If we could dynamically change the anchor points, probably we would have considered the closet point of the barriers that is located within the cone of vision as one end of a spring and the moving agent as the other end. This alternative method is also computationally much more efficient since we consider one spring instead of thousands of them. Kangoroo is a great engine, though it has its limitations as well. Maybe designing a battery for the sake of crowd simulation is the best choice.
Please check my second video and share your comments with me!
Appreciate your comments!
You are right...but, you can check if there is direct line (in a mesuareable angle from movement direction vector) between two points and if that is true -> draw a spring that conects both points. The problem is that I suppose that this dinamic list of springs could make Kangaroo crash or don't work properly...I have never try.
I agree that I have not provided the sight. However, if there is any difference that would be the "cone of vision", which is set to 2*PI here while in reality it is smaller than PI. Here I did not want to do scripting, but by scripting we can also take hold of the vision angle.
That doesn't really have much to do with the way sight functions, since there's no way for it to be obstructed...
Force repulsion I supose...
How are you simulating the sightedness of agents with kangaroo?
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