1. Behavioral animation CSE 3541 Matt Boggus

2. Material recap and trajectory Geometric – Artist specifies translation and rotation over time Physically based – Artist specifies forces acting on objects – Motion equations dictate movement Behavioral – Artist directs autonomous agents Interpolation – Artist draws the scene at the beginning and end of a an interval of time – Intermediate positions are calculated

3. Behavioral Animation Control the motion of one or more objects using virtual actors Goal: realistic or believable motion so that the object appears to be autonomous Matt Lewis’ page on BA http://accad.osu.edu/~mlewis/Class/behavior.html http://accad.osu.edu/~mlewis/Class/behavior.html

4. Behavioral animation Character or object motion based on: – Knowledge of the environment – Aggregate behavior – Primitive behavior – Intelligent behavior – Crowd management

5. Actor properties (position only) Position (x, y) Goal (x g, y g ) V = Goal - Position Next Position = Position + V * dt

6. Actor properties (position and orientation) Position (x, y) Goal (x g, y g ) V target = Goal - Position Orientation (ox, oy) = transform.forward Rotate(θ) In Unity, you can use RotateTowards() Rotate(-θ) Determine which rotation (±θ) orients the actor closer to the goal using dot product

7. Sample code class OrientedAgent2D { // Data Vector3 position; GameObject model;// Use this for geometry and orientation // Methods Update(float deltaTime); TurnLeft(); TurnRight(); MoveForward(); MoveBackward(); };

8. Knowing the environment Vision and other senses – Information available now Memory – Information stored from the past

9. Vision General vision – What can the actor see? – What is everything in sight now? Targeted vision – Can the actor see object X? Computation vs. accuracy – How much of an object needs to be seen to be identified? – Do we need to model visual perception?

10. Omniscience Everything in the scene is known

11. Field of view

12. Field of view – example Orientation Vector (O) Vector from agent to vertex (V) Inside the cone when the angle between O and V is less then or equal to θ/2 Angle of cone = θ

13. Field of view – sample code Vector3 agentPosition, orientation, objectPosition; float visionLimit; Vector3 agentToVertex = objectPosition – agentPosition; agentToVertex.Normalize(); if(Vector3.Dot(agentToVertex,orientation) > visionLimit) // agent can see object

14. Occluded Vision Ray casting with collision detection Sample the environment

15. Target-testing vision (per object) Can the actor see X? Cast a ray How well can the actor see X? Use multiple rays

16. Target-testing vision (alternative) Sample the vision cone Cast multiple rays

17. Lab4 – predator-prey simulation Unbalanced abilities – Vision Distance Field of view – Linear speed (moving forward) – Angular or rotational speed (turning)

18. Spatial Occupancy

19. Other senses Hearing Smell Sensors & signal propagation Spatial occupancy approach Applications

20. Memory What is recorded about the environment Spatial occupancy Transience of objects: time-stamps Memory hierarchy: short-term, long-term

21. Spatial Occupancy doorway transiency wall

22. Aggregate Behavior: Emergent Behavior TypeElementsPhysics Env/Others Intelligence Particles10 2 -10 4 Much/noneNone Flocking10 1 -10 3 Some/someLimited Crowds10 1 -10 2 Little/muchLittle-much Typical qualities

23. Emergent behavior Complex systems and patterns arising out of simple rules Aints – AI ants http://www.youtube.com/watch?v=rsqsZCH36Hk http://www.youtube.com/watch?v=rsqsZCH36Hk

24. Predator Prey vision anatomy

25. Prey-Predator (vision)

26. Prey-Predator (movement – speed and turning)

27. Motion – force based Apply a force on the predator towards the prey when in view Force = c * pos prey - pos pred

28. Motion – kinematic based Determine the closest prey in view then turn towards it and increase forward velocity v old v new

29. Prey-Predator – environment forces Using pure forces May not prevent object penetration Prey can be ‘hidden’ by environmental repulsive forces

30. Flocking, Swarming, Flying Boids http://www.red3d.com/cwr/boids/

31. Local control Rules defined to stay with friends, but avoid bumping into each other Need additional rules for collision avoidance with obstacles

32. Local information

33. Other flocking issues Global control – script flock leader – global migratory urge Negotiating the motion – Separation, alignment, and cohesion may compete/contradict Collision avoidance – Once an object is in sight, start steering to avoid Splitting and rejoining (difficult) – Collision avoidance too strong – flock may never rejoin after split – Flock membership too strong – flock does not split and formation changes Modeling flight

34. Negotiating the motion Forces Or “Reasoning” (e.g. rule-based)

35. Navigating obstacles Problems with repulsive forces

36. Navigating using bounding sphere

37. Navigating Testing for being on a collision path with (bounding) sphere Given: P, V, C, r

38. Finding closest non-colliding point Calculate s,t

39. Modeling flight – common in flocking

40. Modeling flight Geometric flight – dynamic, incremental rigid transformation of an object moving along a tangent to a three dimensional curve

41. Modeling Flight – Lift Air passing above wing most travel longer than air below it. Less pressure above wing = lift

42. Modeling Flight – turn by rolling

43. Modeling Flight – summary Turning is effected by horizontal lift Increasing pitch increases drag Increasing speed increases lift