I'm writing a simulation in which a creature object should be able to move towards some other arbitrary object in the environment, sliding around obstacles rather than doing any intelligent pathfinding. I'm not trying to have it plan a path -- just to move in one general direction, and bounce around obstacles.
It's a 2D environment (overhead view), and every object has a bounding rectangle for collision detection. There is no grid, and I am not looking for A* solution.
I haven't been able to find any tutorials on this kind of "dumb" collision-based pathfinding, so I might not be describing this using the most common terms.
Any recommendations on how to implement this (or links to tutorials)?
Expanding on what Guillaume said about obstacle avoidance, a technique that would work well for you is anti-gravity movement. You treat local obstacles as point sources of antigravity, the destination as gravity, and your computer controlled character will slip (like soap!) around the obstacles to get to the destination.
you can combine two steering algorithm :
seek : you apply a steering force in the direction which is the difference between the current velocity and the desired velocity towards the target
Obstacle Avoidance : you anticipates the vehicle's future using a box whose length is a constant time multiplied by the current velocity of the vehicle. Any obstacle that intersects this box is a potential collision threat. The nearest such threat is chosen for avoidance. To avoid an obstacle, a lateral steering force is applied opposite to the obstacle's center. In addition, a braking (deceleration) force is applied. These forces vary with urgency (the distance from the tip of the box to the point of potential collision). Steering varies linearly, braking varies quadratically.
You can find more on the website "Steering Behaviors For Autonomous Characters"
regards
Guillaume
PS : this assume you're using a point/velocity/acceleration method for the object's movement.
Maybe you could use Pledge's algorithm
Whenever your creature, travelling in vector direction v, collides with a wall whose direction is represented by vector w, the direction that you need to "slide" is given by the vector that is the projection of v onto w. This can be found using
v . w
--------- w
|w|*|w|
where . is the vector dot product and |w| is the magnitude of vector w ( = sqrt(w . w)). If w is a unit vector, this becomes simply
(v . w) w
Using the resulting vector as your creature's speed will mean your creature travels quickly when it just "grazes" the wall, and slowly when it hits the wall nearly dead-on. (This is how most first-person shooter games manage collisions for the human player.)
If instead you want your creature to always travel at full speed, you only need the sign of v . w -- you will always be travelling either in the direction the wall faces (w) or the opposite direction (-w).
The issue that you will have is when your creature hits the wall dead-on. In that case your projected vector will be (0, 0), and you need some other technique to decide which way (w or -w) to go. The usual approach here is A*, although this may be unnecessary if your environment possesses enough structure.
I posted a pathfinding algorithm in C# a while back
Here's the link
You can try and use it as a starting point, ie, you could modify the function that checks the next cell to see if it's valid to check for the obstacles, and you could feed it small intervals instead of the starting and end points, kinda like multiple mini-pahfinding routes.
(The text is in spanish, but you can download the application from the link at the top)
Related
I have a kuka iiwa (7 joint robot arm). Attached to it is a circular aluminum platter with a steel ball on it. The goal of the project (for giggles/ challenge) was to use the internal torque sensors of the robot in order to balance the ball in the middle of the platter. Due to the fact that I was unable/ not allowed to use FRI (fast robot interface) whereby I can control the robot from C at about 3ms feedback loop, I can only update the robot position at about 4Hz... My quick and dirty solution consisted of the following:
Measure the torque on the final two axes of the arm and apply a mapping to generate the ball's position (filtration and hysteresis were well implemented to improve the data quality). If the ball velocity was sufficiently stable, generate a motion that would cancel out that velocity (with an impulse "go to angle and return to neutral position" motion). Overlaid on that was also a small proportional gain which would tend the ball towards the center of the platter.
My question: What is the professional/ correct solution to this situation (where your controller can only hit the system with impulses rather than continuous feedback)?
Here is a picture of the setup:
A slightly dampened negative feedback loop.
Where bal.posX dictates strength y.rot.arm ?
https://en.wikipedia.org/wiki/Control_system
I once coded something alike it, my colleague who's into PLC's called it that.
I did fuzzy logic optimization then..
I am creating a game where the character can jump in the direction opposite of the surface he lands on. For example if he is on the ground he can only jump up. If he is on a right edge he can only jump left...etc etc.. Currently I have set up my SKNodes into leftWall, rightWall, bottomSurface, topSurface and have a huge if/else... this works but will become way more complicated as I add different surfaces with different angles etc...
I thought a better way to implement this would be to find the normal vector direction at the point of contact between the character sprite and a general wallNode sprites.
Can anyone help me determine A) the point of contact between sprites assuming the character has a circle physics body and the walls are always straight edges. and B) the normal to the contact point
thank you!
I don't think the vector or angle of impact will do you much good as your player's jump would likely be in an ark. As such, hitting the same surface at different points of the player's jump ark would yield different results.
I suggest you use unique category bit masks for your surfaces. A more advanced version of that would be to use only one category and utilize the SKSpriteNode's dictionary property to hold the angle value.
Based on the contact data you can then set the correctly angled jump for your player.
How can I implement the A* algorithm on a gridless 2D plane with no nodes or cells? I need the object to maneuver around a relatively high number of static and moving obstacles in the way of the goal.
My current implementation is to create eight points around the object and treat them as the centers of imaginary adjacent squares that might be a potential position for the object. Then I calculate the heuristic function for each and select the best. The distances between the starting point and the movement point, and between the movement point and the goal I calculate the normal way with the Pythagorean theorem. The problem is that this way the object often ignores all obstacle and even more often gets stuck moving back and forth between two positions.
I realize how silly mu question might seem, but any help is appreciated.
Create an imaginary grid at whatever resolution is suitable for your problem: As coarse grained as possible for good performance but fine-grained enough to find (desirable) gaps between obstacles. Your grid might relate to a quadtree with your obstacle objects as well.
Execute A* over the grid. The grid may even be pre-populated with useful information like proximity to static obstacles. Once you have a path along the grid squares, post-process that path into a sequence of waypoints wherever there's an inflection in the path. Then travel along the lines between the waypoints.
By the way, you do not need the actual distance (c.f. your mention of Pythagorean theorem): A* works fine with an estimate of the distance. Manhattan distance is a popular choice: |dx| + |dy|. If your grid game allows diagonal movement (or the grid is "fake"), simply max(|dx|, |dy|) is probably sufficient.
Uh. The first thing that come to my mind is, that at each point you need to calculate the gradient or vector to find out the direction to go in the next step. Then you move by a small epsilon and redo.
This basically creates a grid for you, you could vary the cell size by choosing a small epsilon. By doing this instead of using a fixed grid you should be able to calculate even with small degrees in each step -- smaller then 45° from your 8-point example.
Theoretically you might be able to solve the formulas symbolically (eps against 0), which could lead to on optimal solution... just a thought.
How are the obstacles represented? Are they polygons? You can then use the polygon vertices as nodes. If the obstacles are not represented as polygons, you could generate some sort of convex hull around them, and use its vertices for navigation. EDIT: I just realized, you mentioned that you have to navigate around a relatively high number of obstacles. Using the obstacle vertices might be infeasible with to many obstacles.
I do not know about moving obstacles, I believe A* doesn't find an optimal path with moving obstacles.
You mention that your object moves back and fourth - A* should not do this. A* visits each movement point only once. This could be an artifact of generating movement points on the fly, or from the moving obstacles.
I remember encountering this problem in college, but we didn't use an A* search. I can't remember the exact details of the math but I can give you the basic idea. Maybe someone else can be more detailed.
We're going to create a potential field out of your playing area that an object can follow.
Take your playing field and tilt or warp it so that the start point is at the highest point, and the goal is at the lowest point.
Poke a potential well down into the goal, to reinforce that it's a destination.
For every obstacle, create a potential hill. For non-point obstacles, which yours are, the potential field can increase asymptotically at the edges of the obstacle.
Now imagine your object as a marble. If you placed it at the starting point, it should roll down the playing field, around obstacles, and fall into the goal.
The hard part, the math I don't remember, is the equations that represent each of these bumps and wells. If you figure that out, add them together to get your final field, then do some vector calculus to find the gradient (just like towi said) and that's the direction you want to go at any step. Hopefully this method is fast enough that you can recalculate it at every step, since your obstacles move.
Sounds like you're implementing The Wumpus game based on Norvig and Russel's discussion of A* in Artifical Intelligence: A Modern Approach, or something very similar.
If so, you'll probably need to incorporate obstacle detection as part of your heuristic function (hence you'll need to have sensors that alert your agent to the signs of obstacles, as seen here).
To solve the back and forth issue, you may need to store the traveled path so you can tell if you've already been to a location and have the heurisitic function examine the past N number of moves (say 4) and use that as a tie-breaker (i.e. if I can go north and east from here, and my last 4 moves have been east, west, east, west, go north this time)
I'm working on a 2D Platform game, and I was wondering what's the best (performance-wise) way to implement Surface (Collision) Detection.
So far I'm thinking of constructing a list of level objects constructed of a list of lines, and I draw tiles along the lines.
alt text http://img375.imageshack.us/img375/1704/lines.png
I'm thinking every object holds the ID of the surface that he walks on, in order to easily manipulate his y position while walking up/downhill.
Something like this:
//Player/MovableObject class
MoveLeft()
{
this.Position.Y = Helper.GetSurfaceById(this.SurfaceId).GetYWhenXIs(this.Position.X)
}
So the logic I use to detect "droping/walking on surface" is a simple point (player's lower legs)-touches-line (surface) check
(with some safety approximation
- let`s say 1-2 pixels over the line).
Is this approach OK?
I`ve been having difficulty trying to find reading material for this problem, so feel free to drop links/advice.
Having worked with polygon-based 2D platformers for a long time, let me give you some advice:
Make a tile-based platformer.
Now, to directly answer your question about collision-detection:
You need to make your world geometry "solid" (you can get away with making your player object a point, but making it solid is better). By "solid" I mean - you need to detect if the player object is intersecting your world geometry.
I've tried "does the player cross the edge of this world geometry" and in practice is doesn't work (even though it might seem to work on paper - floating point precision issues will not be your only problem).
There are lots of instructions online on how to do intersection tests between various shapes. If you're just starting out I recommend using Axis-Aligned Bounding Boxes (AABBs).
It is much, much, much, much, much easier to make a tile-based platformer than one with arbitrary geometry. So start with tiles, detect intersections with AABBs, and then once you get that working you can add other shapes (such as slopes).
Once you detect an intersection, you have to perform collision response. Again a tile-based platformer is easiest - just move the player just outside the tile that was collided with (do you move above it, or to the side? - it will depend on the collision - I will leave how to do this is an exercise).
(PS: you can get terrific results with just square tiles - look at Knytt Stories, for example.)
Check out how it is done in the XNA's Platformer Starter Kit Project. Basically, the tiles have enum for determining if the tile is passable, impassable etc, then on your level you GetBounds of the tiles and then check for intersections with the player and determine what to do.
I've had wonderful fun times dealing with 2D collision detection. What seems like a simple problem can easily become a nightmare if you do not plan it out in advance.
The best way to do this in a OO-sense would be to make a generic object, e.g. classMapObject. This has a position coordinate and slope. From this, you can extend it to include other shapes, etc.
From that, let's work with collisions with a Solid object. Assuming just a block, say 32x32, you can hit it from the left, right, top and bottom. Or, depending on how you code, hit it from the top and from the left at the same time. So how do you determine which way the character should go? For instance, if the character hits the block from the top, to stand on, coded incorrectly you might inadvertently push the character off to the side instead.
So, what should you do? What I did for my 2D game, I looked at the person's prior positioning before deciding how to react to the collision. If the character's Y position + Height is above the block and moving west, then I would check for the top collision first and then the left collision. However, if the Character's Y position + height is below the top of the block, I would check the left collision.
Now let's say you have a block that has incline. The block is 32 pixels wide, 32 pixels tall at x=32, 0 pixels tall at x=0. With this, you MUST assume that the character can only hit and collide with this block from the top to stand on. With this block, you can return a FALSE collision if it is a left/right/bottom collision, but if it is a collision from the top, you can state that if the character is at X=0, return collision point Y=0. If X=16, Y=16 etc.
Of course, this is all relative. You'll be checking against multiple blocks, so what you should do is store all of the possible changes into the character's direction into a temporary variable. So, if the character overlaps a block by 5 in the X direction, subtract 5 from that variable. Accumulate all of the possible changes in the X and Y direction, apply them to the character's current position, and reset them to 0 for the next frame.
Good luck. I could provide more samples later, but I'm on my Mac (my code is on a WinPC) This is the same type of collision detection used in classic Mega Man games IIRC. Here's a video of this in action too : http://www.youtube.com/watch?v=uKQM8vCNUTM
You can try to use one of physics engines, like Box2D or Chipmunk. They have own advanced collision detection systems and a lot of different bonuses. Of course they don't accelerate your game, but they are suitable for most of games on any modern devices
It is not that easy to create your own collision detection algorithm. One easy example of a difficulty is: what if your character is moving at a high enough velocity that between two frames it will travel from one side of a line to the other? Then your algorithm won't have had time to run in between, and a collision will never be detected.
I would agree with Tiendil: use a library!
I'd recommend Farseer Physics. It's a great and powerful physics engine that should be able to take care of anything you need!
I would do it this way:
Strictly no lines for collision. Only solid shapes (boxes and triangles, maybe spheres)
2D BSP, 2D partitioning to store all level shapes, OR "sweep and prune" algorithm. Each of those will be very powerfull. Sweep and prune, combined with insertion sort, can easily thousands of potentially colliding objects (if not hundreds of thousands), and 2D space partitioning will allow to quickly get all nearby potentially colliding shapes on demand.
The easiest way to make objects walk on surfaces is to make then fall down few pixels every frame, then get the list of surfaces object collides with, and move object into direction of surface normal. In 2d it is a perpendicular. Such approach will cause objects to slide down on non-horizontal surfaces, but you can fix this by altering the normal slightly.
Also, you'll have to run collision detection and "push objects away" routine several times per frame, not just once. This is to handle situations if objects are in a heap, or if they contact multiple surfaces.
I have used a limited collision detection approach that worked on very different basis so I'll throw it out here in case it helps:
A secondary image that's black and white. Impassible pixels are white. Construct a mask of the character that's simply any pixels currently set. To evaluate a prospective move read the pixels of that mask from the secondary image and see if a white one comes back.
To detect collisions with other objects use the same sort of approach but instead of booleans use enough depth to cover all possible objects. Draw each object to the secondary entirely in the "color" of it's object number. When you read through the mask and get a non-zero pixel the "color" is the object number you hit.
This resolves all possible collisions in O(n) time rather than the O(n^2) of calculating interactions.
I have a field filled with obstacles, I know where they are located, and I know the robot's position. Using a path-finding algorithm, I calculate a path for the robot to follow.
Now my problem is, I am guiding the robot from grid to grid but this creates a not-so-smooth motion. I start at A, turn the nose to point B, move straight until I reach point B, rinse and repeat until the final point is reached.
So my question is: What kind of techniques are used for navigating in such an environment so that I get a smooth motion?
The robot has two wheels and two motors. I change the direction of the motor by turning the motors in reverse.
EDIT: I can vary the speed of the motors basically the robot is an arduino plus ardumoto, I can supply values between 0-255 to the motors on either direction.
You need feedback linearization for a differentially driven robot. This document explains it in Section 2.2. I've included relevant portions below:
The simulated robot required for the
project is a differential drive robot
with a bounded velocity. Since
the differential drive robots are
nonholonomic, the students are encouraged to use feedback linearization to
convert the kinematic control output
from their algorithms to control the
differential drive robots. The
transformation follows:
where v, ω, x, y are the linear,
angular, and kinematic velocities. L
is an offset length proportional to the
wheel base dimension of the robot.
One control algorithm I've had pretty good results with is pure pursuit. Basically, the robot attempts to move to a point along the path a fixed distance ahead of the robot. So as the robot moves along the path, the look ahead point also advances. The algorithm compensates for non-holonomic constraints by modeling possible paths as arcs.
Larger look ahead distances will create smoother movement. However, larger look ahead distances will cause the robot to cut corners, which may collide with obstacles. You can fix this problem by implementing ideas from a reactive control algorithm called Vector Field Histogram (VFH). VFH basically pushes the robot away from close walls. While this normally uses a range finding sensor of some sort, you can extrapolate the relative locations of the obstacles since you know the robot pose and the obstacle locations.
My initial thoughts on this(I'm at work so can't spend too much time):
It depends how tight you want or need your corners to be (which would depend on how much distance your path finder gives you from the obstacles)
Given the width of the robot you can calculate the turning radius given the speeds for each wheel. Assuming you want to go as fast as possible and that skidding isn't an issue, you will always keep the outside wheel at 255 and reduce the inside wheel down to the speed that gives you the required turning radius.
Given the angle for any particular turn on your path and the turning radius that you will use, you can work out the distance from that node where you will slow down the inside wheel.
An optimization approach is a very general way to handle this.
Use your calculated path as input to a generic non-linear optimization algorithm (your choice!) with a cost function made up of closeness of the answer trajectory to the input trajectory as well as adherence to non-holonomic constraints, and any other constraints you want to enforce (e.g. staying away from the obstacles). The optimization algorithm can also be initialised with a trajectory constructed from the original trajectory.
Marc Toussaint's robotics course notes are a good source for this type of approach. See in particular lecture 7:
http://userpage.fu-berlin.de/mtoussai/teaching/10-robotics/