xiaoyuan tu and demetri terzopoulos, dept. of cs, university of toronto
DESCRIPTION
Artificial Fishes: Physics, Locomotion, Perception, Behavior. Mar. 30, 2001. Xiaoyuan Tu and Demetri Terzopoulos, Dept. of CS, University of Toronto. Presentation by Siddharth Dalal. Intro & Background. What do fish do? eat, survive, when compelled by their libidos…. - PowerPoint PPT PresentationTRANSCRIPT
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Mar. 30, 2001
Xiaoyuan Tu and Demetri Terzopoulos,
Dept. of CS, University of Toronto
Artificial Fishes: Physics, Locomotion, Perception, Behavior
Presentation by Siddharth Dalal
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Intro & Background
• What do fish do?– eat, survive, when compelled by their libidos….
• Physics based graphic modeling
• Worm Dynamics, facial model– more sophisticated spring mass model
• advanced behavioral animation
Any fish is good if caught on the hook.
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Overview
Intention focuses sensory data causing behavior
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Fishics 1 - Mechanics• Spring Mass Model
wiiii fw
dt
dxq
dt
xdm
2
2
m = massx = positionq = damping factorw = net force due to springsf = external force
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Fishics 2 - Hydrodynamics• Swimming - Muscles + Hydrodynamics
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Fishics 3 - Motor Controllers• Swim MC• Left and right MC
• Anterior and Posterior of fish - r1, s1, r2, s2• Max params scaled from 0 - 1 to produce varying speeds
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Sensory Perception
• Two on board environment sensors:– Vision Sensor - extracts information from scene
geometry, object database, physical simulation. Cyclopean(?) vision - 300o viewing angle.
– Temperature sensor - senses ambient temp. at center of body
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Behavio(u)r 1
• Intention based on– Habits– Mental State– Incoming Sensory Information
• decides behavior routine
• incremental - needs memory
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Behavior 2 - Habits and Mind
• Habits - does fish like brightness, schooling, male or female (yes this is in habits)
• Mental State– Three mental states - HLF - hunger, libido, fear– H= min[1-n(t)R(Δt)/α, 1]– L=min[s(Δt)(1-H(t)), 1]– F=min[Σf, 1], f=min[D/d(t), 1]
(Fish like sex after dinner )
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Intentions 1• Intentions
– avoid,– escape– school– eat– mate– leave– wander
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Intentions 2
• Features of Generator– Persistence in intentions - no dithering– focusser - focus on most important intention
• Create ‘abnormal fish’– warp intentions
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Intentions 3
• Behavior routines:– eight - avoid static obstacle, avoid fish, eat,
mate, leave, wander, escape, school– chasing target subroutine– other subroutines - looping?, circling,
ascending?, nuzzling
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Fish Type = Warped Intentions
• Artificial Fish Types– Predators
• don’t escape, mate or school
• always cruise, so don’t leave
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Fish Type = Prey Fish Grey Fish
• Artificial Fish Types– Prey
• school
• evade predators
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Pacifists
• Artificial Fish Types– Pacifist
• no school, no escape
• just mate
• complex mating behavior implemented…– fish i chooses partner j
– criteria if i is female/male
– looping, circling, chasing-target, nuzzling
– etc.
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Result
• 10 fish, 15 food particles, 5 static obstacles at 4fps on SGI R4400 Indigo2
• Future:– reproduction– other work
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Links
• http://www.dgp.toronto.edu/people/tu/tu.html• http://citeseer.nj.nec.com/tu94artificial.html• http://www.cs.toronto.edu/~dt/
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Guests and fish start to stink after two days.