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{{Short description|Term in computer science}}

{{About|collision detection in computational geometry|collision detection in computer networks|Carrier-sense multiple access with collision detection}}

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'''Collision detection''' is the [[computational problem]] of detecting an [[Intersection (geometry)|intersection]] of two or more objects in virtual space. More precisely, it deals with the questions of ''if'', ''when'' and ''where'' two or more objects intersect. Collision detection is a classic problem of [[computational geometry]] with applications in [[computer graphics]], [[physical simulation]], [[Videovideo game|video games]]s, [[robotics]] (including [[autonomous driving]]) and [[computational physics]]. Collision detection [[algorithm]]s can be divided into operating on 2D or 3D spatial objects.<ref>{{cite journal|url=https://hal.inria.fr/inria-00394479/document|title=Collision Detection for Deformable Objects|year=2005|doi=10.1111/j.1467-8659.2005.00829.x|last1=Teschner|first1=M.|last2=Kimmerle|first2=S.|last3=Heidelberger|first3=B.|last4=Zachmann|first4=G.|last5=Raghupathi|first5=L.|last6=Fuhrmann|first6=A.|last7=Cani|first7=M.-P.|last8=Faure|first8=F.|last9=Magnenat-Thalmann|first9=N.|last10=Strasser|first10=W.|last11=Volino|first11=P.|journal=Computer Graphics Forum|volume=24|pages=61–81|s2cid=1359430|citeseerx=10.1.1.58.2505}}</ref>

== Overview ==

[[Image:Billiards balls.jpg|right|200px|thumb|Billiards balls hitting each other in a virtual space are a classic example where collision detection computations are needed.]]Collision detection is closely linked to calculating the [[Euclidean distance|distance]] between objects, as two objects (or more) intersect when the distance between them reaches zero or even becomes negative.<ref>{{Cite book |url=https://www.csun.edu/~ctoth/Handbook/HDCG3.html |title=Handbook of discrete and computational geometry |date=2018 |publisher=CRC Press, Taylor & Francis Group, a Chapman & Hall book |isbn=978-1-4987-1139-5 |editor-last=Goodman |editor-first=Jacob E. |edition=3rd |series=Discrete mathematics and its applications |___location=Boca Raton London New York |chapter=39 |editor-last2=O'Rourke |editor-first2=Joseph |editor-last3=Tóth |editor-first3=Csaba D.}}</ref> Negative distance indicates that one object has penetrated another. Performing collision detection requires more context than just the distance between the objects.

Accurately identifying the points of contact on both objects' surfaces is also essential for the computation of a physically accurate [[collision response]]. The complexity of this task increases with the level of detail in the objects' representations: the more intricate the model, the greater the computational cost.<ref name=":col0">{{Cite journalbook |lastlast1=Andrews |firstfirst1=Sheldon |last2=Erleben |first2=Kenny |last3=Ferguson |first3=Zachary |date=2022-08-02 |titlechapter=Contact and friction simulation for computer graphics |date=2022-08-02 |title=ACM SIGGRAPH 2022 Courses |chapter-url=https://dl.acm.org/doi/10.1145/3532720.3535640 |journal=SIGGRAPH ’22 Courses |language=en |publisher=ACM |pages=1–172 |doi=10.1145/3532720.3535640 |isbn=978-1-4503-9362-1}}</ref>

Collision detection frequently involves dynamic objects, adding a temporal dimension to distance calculations. Instead of simply measuring distance between static objects, collision detection algorithms often aim to determine whether the objects’ motion will bring them to a point in time when their distance is zero—an operation that adds significant computational overhead.<ref name=":col1">{{Cite journalbook |lastlast1=Hadap |firstfirst1=Sunil |last2=Eberle |first2=Dave |last3=Volino |first3=Pascal |last4=Lin |first4=Ming C. |last5=Redon |first5=Stephane |last6=Ericson |first6=Christer |chapter=Collision detection and proximity queries |date=2004-08-08 |title=CollisionACM detectionSIGGRAPH and2004 proximityCourse queriesNotes |chapter-url=https://dl.acm.org/doi/10.1145/1103900.1103915 |journal=SIGGRAPH ’04 Courses |language=en |publisher=ACM |pages=15 |doi=10.1145/1103900.1103915 |isbn=978-1-4503-7801-7}}</ref><ref name=":col0" />

In collision detection involving multiple objects, a naive approach would require detecting collisions for all pairwise combinations of objects. As the number of objects increases, the number of required comparisons grows rapidly: for <math>n</math> objects, <math display="">{n(n-1)}/{2}</math> intersection tests are needed with a naive approach. This quadratic growth makes such an approach computationally expensive as <math>n</math> increases.<ref name=":col1" /><ref name=":0">{{Cite journalbook |lastlast1=Cohen |firstfirst1=Jonathan D. |last2=Lin |first2=Ming C. |last3=Manocha |first3=Dinesh |last4=Ponamgi |first4=Madhav |date=1995 |titlechapter=I-COLLIDE: anAn interactive and exact collision detection system for large-scale environments |urldate=http://portal.acm.org/citation.cfm?doid=199404.1994371995 |journaltitle=I3D '95: Proceedings of the 1995 symposium on Interactive 3D graphics - SI3D '95 |chapter-url=http://portal.acm.org/citation.cfm?doid=199404.199437 |language=en |publisher=ACM Press |pages=189–ff. |doi=10.1145/199404.199437 |isbn=978-0-89791-736-0}}</ref>

Due to the complexity mentioned above, collision detection is a computationally intensive process. Nevertheless, it is essential for interactive applications like video games, robotics, and real-time physics engines. To manage these computational demands, extensive efforts have gone into optimizing collision detection algorithms.

A commonly used approach towards accelerating the required computations is to divide the process into two phases: the '''broad phase''' and the '''narrow phase'''.<ref name=":col1" /><ref>{{Cite book |lastlast1=Akenine-Möller |firstfirst1=Tomas |url=https://www.realtimerendering.com |title=Real-time rendering |last2=Haines |first2=Eric |last3=Hoffman |first3=Naty |last4=Pesce |first4=Angelo |last5=Iwanicki |first5=Michał |last6=Hillaire |first6=Sébastien |date=2018 |publisher=CRC Press, Taylor & Francis Group |isbn=978-1-138-62700-0 |edition=4th |series=An A K Peters book |___location=Boca Raton London New York}}</ref> The broad phase aims to answer the question of whether objects might collide, using a conservative but efficient approach to rule out pairs that clearly do not intersect, thus avoiding unnecessary calculations.

Objects that cannot be definitively separated in the broad phase are passed to the narrow phase. Here, more precise algorithms determine whether these objects actually intersect. If they do, the narrow phase often calculates the exact time and ___location of the intersection.

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=== Spatial partitioning ===

Several approaches can be grouped under the [[spatial partitioning]] umbrella, which includes [[octree]]s (for 3D), [[Quadtree|quadtreesquadtree]]s (for 2D), [[binary space partitioning]] (or BSP trees) and other, similar approaches. If one splits space into a number of simple cells, and if two objects can be shown not to be in the same cell, then they need not be checked for intersection. Dynamic scenes and deformable objects require updating the partitioning which can add overhead.

===Bounding volume hierarchy===

[[Bounding volume hierarchy|Bounding Volume Hierarchy]] (BVH) is a tree structure over a set of [[Collision detection#Bounding volumes|bounding volumes]]. Collision is determined by doing a tree traversal starting from the root. If a the bounding volume of the root doesn't intersect with the object of interest, the traversal can be stopped. If, however there is an intersection, the traversal proceeds and checks the branches for each there is an intersection. Branches for which there is no intersection with the bounding volume can be culled from further intersection test. Therefore, multiple objects can be determined to not intersect at once. BVH can be used with deformable objects such as cloth or soft-bodies but the volume hierarchy has to be adjusted as the shape deforms. For deformable objects we need to be concerned about self-collisions or self intersections. BVH can be used for that end as well. Collision between two objects is computed by computing intersection between the bounding volumes of the root of the tree as there are collision we dive into the sub-trees that intersect. Exact collisions between the actual objects, or its parts (often triangles of a [[triangle mesh]]) need to be computed only between intersecting leaves.<ref>

{{cite journal |last1=Klosowski |first1=James T |last2=Held |first2=Martin |last3=Mitchell |first3=Joseph S.B. |last4=Sowizral |first4=Henry |last5=Zikan |first5=Karel |date=1998 |title=Efficient collision detection using bounding volume hierarchies of k-DOPs |journal=IEEE Transactions on Visualization and Computer Graphics |publisher=IEEE |volume=4 |issue=1 |pages=21–36 |doi=10.1109/2945.675649}}

</ref> The same approach works for pair wise collision and self-collisions.

=== Exploiting temporal coherence ===

During the broad-phase, when the objects in the world move or deform, the data-structures used to cull collisions have to be updated. In cases where the changes between two frames or time-steps are small and the objects can be approximated well with [[axis-aligned bounding box]]es, the [[sweep and prune]] algorithm<ref name=":0" /> can be a suitable approach.

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In many applications, the configuration of physical bodies from one time step to the next changes very little. Many of the objects may not move at all. Algorithms have been designed so that the calculations done in a preceding time step can be reused in the current time step, resulting in faster completion of the calculation.

At the coarse level of collision detection, the objective is to find pairs of objects which might potentially intersect. Those pairs will require further analysis. An early high performance algorithm for this was developed by [[Ming C. Lin]] at the [[University of California, Berkeley]] [http://www.cs.berkeley.edu/~jfc/mirtich/collDet.html], who suggested using [[axis-aligned bounding box]]es for all ''n'' bodies in the scene.

Each box is represented by the product of three intervals (i.e., a box would be <math>I_1 \times I_2 \times I_3=[a_1,b_1] \times [a_2,b_2] \times [a_3,b_3]</math>). A common algorithm for collision detection of bounding boxes is [[sweep and prune]]. Observe that two such boxes, <math>I_1 \times I_2 \times I_3</math> and <math>J_1 \times J_2 \times J_3</math> intersect [[If and only if|if, and only if]], <math>I_1</math> intersects <math>J_1</math>, <math>I_2</math> intersects <math>J_2</math> and <math>I_3</math> intersects <math>J_3</math>. It is supposed that, from one time step to the next, if <math>I_k</math> and <math>J_k</math> intersect, then it is very likely that at the next time step they will still intersect. Likewise, if they did not intersect in the previous time step, then they are very likely to continue not to.

So we reduce the problem to that of tracking, from frame to frame, which intervals do intersect. We have three lists of intervals (one for each axis) and all lists are the same length (since each list has length <math>n</math>, the number of bounding boxes.) In each list, each interval is allowed to intersect all other intervals in the list. So for each list, we will have an <math>n \times n</math> [[matrix (math)|matrix]] <math>M=(m_{ij})</math> of zeroes and ones: <math>m_{ij}</math> is 1 if intervals <math>i</math> and <math>j</math> intersect, and 0 if they do not intersect.

By our assumption, the matrix <math>M</math> associated to a list of intervals will remain essentially unchanged from one time step to the next. To exploit this, the list of intervals is actually maintained as a list of labeled endpoints. Each element of the list has the coordinate of an endpoint of an interval, as well as a unique integer identifying that interval. Then, we [[sorting algorithm|sort]] the list by coordinates, and update the matrix <math>M</math> as we go. It's not so hard to believe that this algorithm will work relatively quickly if indeed the configuration of bounding boxes does not change significantly from one time step to the next.

In the case of deformable bodies such as cloth simulation, it may not be possible to use a more specific pairwise pruning algorithm as discussed below, and an ''n''-body pruning algorithm is the best that can be done.

Several key observation make the implementation efficient: Two bounding-boxes intersect [[If and only if|if, and only if]], there is overlap along all three axes; overlap can be determined, for each axis separately, by sorting the intervals for all the boxes; and lastly, between two frames updates are typically small (making sorting algorithms optimized for almost-sorted lists suitable for this application). The algorithm keeps track of currently intersecting boxes, and as objects move, re-sorting the intervals helps keep track of the status.<ref>{{Cite book |last=Ericson |first=Christer |url=https://realtimecollisiondetection.net/books/rtcd/ |title=Real-time collision detection |date= 22 December 2004|publisher=Elsevier |isbn=978-1-55860-732-3 |edition=Nachdr. |series=Morgan Kaufmann series in interactive 3D technology |___location=Amsterdam Heidelberg |pages=329–338}}</ref>

If an upper bound can be placed on the velocity of the physical bodies in a scene, then pairs of objects can be pruned based on their initial distance and the size of the time step.

=== Pairwise pruning ===

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Many variants of the algorithms are obtained by choosing something other than a sphere for <math>B(T)</math>. If one chooses [[axis-aligned bounding box]]es, one gets AABBTrees. [[Oriented bounding box]] trees are called OBBTrees. Some trees are easier to update if the underlying object changes. Some trees can accommodate higher order primitives such as [[Spline (mathematics)|spline]]s instead of simple triangles.

== Narrow phase ==

Objects that cannot be definitively separated in the broad phase are passed to the narrow phase. In this phase, the objects under consideration are relatively close to each other. Still, attempts to quickly determine if a full intersection is needed are employed first. This step is sometimes referred to as mid-phase.<ref name=":col1" /> Once these tests passed (e.g. the pair of objects may be colliding) more precise algorithms determine whether these objects actually intersect. If they do, the narrow phase often calculates the exact time and ___location of the intersection.

===Bounding volumes===

A quick way to potentially avoid a needless expensive computation is to check if the bounding volume enclosing the two objects intersect. If they don't, there is notno need to check the actual objects. However, if the [[bounding volume|bounding volumes]] do intersect, the more expensive computation has to be performed. In order for the bounding-volume test to add value, two properties need to be balanced: a) the cost of intersecting the bounding volume needs to be low and b) the bounding volume needs to be tight enough so that the number of 'false positive' intersection will be low. A false positive intersection in this case means that the bounding volumevolumes intersect but the actual objects do not. Different bounding volume types offer different trade-offs for these properties.

[[Minimum bounding box#Axis-aligned minimum bounding box|Axis-Align Bounding Boxes (AABB)]] and [[cuboid]]s are popular due to their simplicity and quick intersection tests. <ref>{{cite web |author=Caldwell, Douglas R. |date=2005-08-29 |title=Unlocking the Mysteries of the Bounding Box |url=http://www.stonybrook.edu/libmap/coordinates/seriesa/no2/a2.htm |url-status=dead |archive-url=https://web.archive.org/web/20120728180104/http://www.stonybrook.edu/libmap/coordinates/seriesa/no2/a2.htm |archive-date=2012-07-28 |access-date=2014-05-13 |publisher=US Army Engineer Research & Development Center, Topographic Engineering Center, Research Division, Information Generation and Management Branch}}</ref> Bounding volumes such as [[Minimum bounding box#Arbitrarily oriented minimum bounding box| Oriented Bounding Boxes (OBB)]], [[Bounding volume#Common types|K-DOPs]] and Convex-hulls offer a tighter approximation of the enclosed shape at the expense of a more elaborate intersection test.

Bounding volumes are typically used in the early (pruning) stage of collision detection, so that only objects with overlapping bounding volumes need be compared in detail.<ref>{{cite journal |author=Gan B, Dong Q |date=2022 |title=An improved optimal algorithm for collision detection of hybrid hierarchical bounding box |url=https://www.researchgate.net/publication/348937861 |journal=Evolutionary Intelligence |volume=15 |issue=4 |pages=2515–2527 |doi=10.1007/s12065-020-00559-6}}</ref> Computing collision or overlap between bounding volumes involves additional computations, therefore, in order for it to beneficial we need the bounding volume to be relatively tight and the computation overhead to due the collisions to be low.

=== Exact pairwise collision detection ===

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OnceObjects we'refor donewhich pruning, weapproaches arecould leftnot withrule aout numberthe possibility of candidatea collision pairshave to checkundergo foran exact collision detection computation.

==== Collision detection between convex objects ====

A basic observation is that for any two [[convex set|convex]] objects which are disjoint, one can find a plane in space so that one object lies completely on one side of that plane, and the other object lies on the opposite side of that plane. This allows the development of very fast collision detection algorithms for convex objects.

BetterAccording methodsto havethe since[[Hyperplane separation theorem|separating planes theorem]], for any two disjoint [[convex set|convex]] objects, there exists a plane so that one object lies completely on one side of that plane, and the other object lies on the opposite side of beenthat developedplane. This Veryproperty fastallows the development of efficient collision detection algorithms between convex objects. Several algorithms are available for finding the closest points on the surface of two convex polyhedral objects. - and determining collision. Early work by [[Ming C. Lin]]<ref name=":1">{{cite web |author=Lin, Ming C |year=1993 |title=Efficient Collision Detection for Animation and Robotics (thesis) |url=https://wwwx.cs.unc.edu/~geom/papers/documents/dissertations/lin93.pdf |archive-url=https://web.archive.org/web/20140728124049/https://wwwx.cs.unc.edu/~geom/papers/documents/dissertations/lin93.pdf |archive-date=2014-07-28 |publisher=University of California, Berkeley}}

</ref> that used a variation on the [[simplex algorithm]] from [[linear programming]] and the [[Gilbert-Johnson-Keerthi distance algorithm]]<ref>{{Cite journal |last1=Gilbert |first1=E.G. |last2=Johnson |first2=D.W. |last3=Keerthi |first3=S.S. |date=1988 |title=A fast procedure for computing the distance between complex objects in three-dimensional space |url=https://graphics.stanford.edu/courses/cs448b-00-winter/papers/gilbert.pdf |journal=IEEE Journal on Robotics and Automation |volume=4 |issue=2 |pages=193–203 |doi=10.1109/56.2083}}</ref> are two such examples. These algorithms approach constant time when applied repeatedly to pairs of stationary or slow-moving objects, and every step is initialized from the previous collision check.<ref name=":1" />

Early work in this area involved "[[Separating axis theorem|separating plane]]" methods. Two triangles collide essentially only when they can not be separated by a plane going through three vertices. That is, if the triangles are <math>{v_1,v_2,v_3}</math> and <math>{v_4,v_5,v_6}</math> where each <math>v_j</math> is a vector in <math>\mathbb R^3</math>, then we can take three vertices, <math>v_i,v_j,v_k</math>, find a plane going through all three vertices, and check to see if this is a separating plane. If any such plane is a separating plane, then the triangles are deemed to be disjoint. On the other hand, if none of these planes are separating planes, then the triangles are deemed to intersect. There are twenty such planes.

If the triangles are coplanar, this test is not entirely successful. One can add some extra planes, for instance, planes that are [[normal (geometry)|normal]] to triangle edges, to fix the problem entirely. In other cases, objects that meet at a flat face must necessarily also meet at an angle elsewhere, hence the overall collision detection will be able to find the collision.

Better methods have since been developed. Very fast algorithms are available for finding the closest points on the surface of two convex polyhedral objects. Early work by [[Ming C. Lin]]<ref>{{cite web |author=Lin, Ming C |year=1993 |title=Efficient Collision Detection for Animation and Robotics (thesis) |url=https://wwwx.cs.unc.edu/~geom/papers/documents/dissertations/lin93.pdf |archive-url=https://web.archive.org/web/20140728124049/https://wwwx.cs.unc.edu/~geom/papers/documents/dissertations/lin93.pdf |archive-date=2014-07-28 |publisher=University of California, Berkeley}}

</ref> used a variation on the [[simplex algorithm]] from [[linear programming]]. The [[Gilbert-Johnson-Keerthi distance algorithm]] has superseded that approach. These algorithms approach constant time when applied repeatedly to pairs of stationary or slow-moving objects, when used with starting points from the previous collision check.

The result of all this algorithmic work is that collision detection can be done efficiently for thousands of moving objects in real time on typical personal computers and game consoles.

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=== Collision detection in computer simulation ===

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Physical simulators differ in the way they react on a collision. Some use the softness of the material to calculate a force, which will resolve the collision in the following time steps like it is in reality. This is very CPU intensive for low softness materials. Some simulators estimate the time of collision by [[linear interpolation]], [[Rollback (data management)|roll back]] the simulation, and calculate the collision by the more abstract methods of [[conservation laws]].

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In many cases for video games, approximating the characters by a point is sufficient for the purpose of collision detection with the environment. In this case, [[binary space partitioning]] trees provide a viable, efficient and simple algorithm for checking if a point is embedded in the scenery or not. Such a data structure can also be used to handle "resting position" situation gracefully when a character is running along the ground. Collisions between characters, and collisions with projectiles and hazards, are treated separately.

A robust simulator is one that will react to any input in a reasonable way. For instance, if we imagine a high speed [[Racing game|racecar video game]], from one simulation step to the next, it is conceivable that the cars would advance a substantial distance along the race track from one simulation step to the next. If there is a shallow obstacle on the track (such as a brick wall), it is not entirely unlikely that the car will completely leap over it, and this is very undesirable. In other instances, the "fixing" that posteriori algorithms require isn't implemented correctly, resulting in [[software bug|bug]]s that can trap characters in walls or allow them to pass through them and fall into an endless void where there may or may not be a deadly [[bottomless pit (video gaming)|bottomless pit]], sometimes referred to as "black hell", "blue hell", or "green hell", depending on the predominant color. These are the hallmarks of a failing collision detection and physical simulation system. ''[[Big Rigs: Over the Road Racing]]'' is an infamous example of a game with a failing or possibly missing collision detection system.

==== Hitbox ====<!-- Deleted image removed: [[File:GearheadsCollisionBoxSize.png|thumb|A [[Debug menu|debug]] dialogue box in ''[[Gearheads (video game)|Gearheads]]'' controlling an object's hitbox {{Deletable file-caption|Tuesday, 9 July 2024|F7}}]] -->

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==See also==

{{div col}}

* [[Chazelle polyhedron]]

* [[Collision response]]

* [[Hit-testing]]

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==External links==

* [https://css-tricks.com/worlds-collide-keyframe-collision-detection-using-style-queries/ Collision detection in CSS animations]

* [http://gamma.cs.unc.edu/research/collision/ University of North Carolina at Chapel Hill collision detection research website]

* [http://web.comlab.ox.ac.uk/oucl/work/stephen.cameron/distances/ Prof. Steven Cameron (Oxford University) web site on collision detection]

* [http://demonstrations.wolfram.com/HowToAvoidACollision/ How to Avoid a Collision] by George Beck, [[Wolfram Demonstrations Project]].

* {{usurped|1=[https://web.archive.org/web/20130108211242/http://geomalgorithms.com/a08-_containers.html Bounding boxes and their usage]}}

* [http://programmerart.weebly.com/separating-axis-theorem.html Separating Axis Theorem]

* [https://docs.unity3d.com/ScriptReference/Collision.html Unity 3D Collision]

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[[Category:Computer graphics]]

[[Category:Video game development]]

[[Category:Robotics]]

[[Category:Computer physics engines]]

[[Category:Robotics engineering]]