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Extending the Basic FSM A Hierarchical FSM Example • Extending states • Begin-end end block BeginDoAction(); DoActions(); EndDoAction(); Gather Treasure Monster dead Monster in sight No monster Flee • Stacks & FSMs • Stack-based “history” of FSMs • “Remember” the sequence of states passed through • “Retrace” its steps at will • Hierarchical FSM • Polymorphic FSMs • Fuzzy State Machine • Combined with fuzzy logic Find Treasure Take Treasure Go To Treasure Fight Find Treasure Gather Treasure Live Stack Cornered Active FSM 55 56 Another Hierarchical FSM Example Done Patrol Done Noise Investigate Saw Enemy Saw Enemy Attack Motion Behavior • Action selection • Steering • Locomotion Patrol Go to A Look for Intruders Go to B Look for Intruders Investigate noise Report Noise Go Over To Noise noise Look for Intruders False Alarm! A Hierarchy of Motion Behavior 57 58 Action Selection • Game AI engine • State machine • Discussed in “Finite State Machine” section • Goals • Planning • Strategy • Scripting • Assigned by players • Players’ input Steering • Path determination • Path finding or path planning • Discussed in “Path Finding” • Behaviors • Seek & flee • Pursuit & evasion • Obstacle avoidance • Wander • Path following • Unaligned collision avoidance • Group steering 59 60 10
Locomotion • Character physically-based models • Movement • Turn right, move forward, … • Animation • By artists • Implemented / managed by game engine A Simple Vehicle Model (1/2) • A point mass • Linear momentum • No rotational momentum • Parameters • Mass • Position • Velocity • Modified by applied forces • Max speed • Top speed of a vehicle • Max steering force • Self-applied • Orientation • Car • Aircraft 61 62 A Simple Vehicle Model (2/2) • Local space • Origin • Forward • Up • Side • Steering forces • Asymmetrical • Thrust • Braking • Steering • Velocity alignment • No slide, spin, … • Turn Euler Integration • The approach : • Steer_force = Truncate(streer_direction, , Max_force) • Acceleration = Steer_force / mass • Velocity = Truncate(Velocity + Acceleration, Max_speed) • Position = Position + Velocity 63 64 Seek & Flee Behaviors Arrival Behavior • Pursuit to a static target • Steer a character toward to a target position • “A A moth buzzing a light bulb” • Flee • Inverse of seek • Variants • Arrival • Pursuit to a moving target • Seek Steering force • desired_velocity = normalize(target - position)*max_speed • steering = desired_velocity – velocity 65 • One of the idea : a stopping radius • Outside the radius, arrival is identical to seek • Inside the radius, the speed is ramped down to zero • target_offset = target – position • distance = length(target_offset) • ramped_speed = max_speed*(distance/slowing_distance) • clipped_speed = minimum(ramped_speed, max_speed) • desired_velocity = (clipped_speed/distance)*target_offset • steering = desired_velocity – velocity 66 11
Page 1 and 2: Contents • Search • Path findin
Page 3 and 4: Heuristic Search (2/2) • When we
Page 5 and 6: A* Algorithm (4/4) • State • Lo
Page 7 and 8: Implement FSM • Code-based FSM
Page 9: Event-driven Processing Model • D
Page 13 and 14: Steering Behaviors for Groups of Ch

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