1. Autonomous Dynamically Simulated Creatures for Virtual Environments Paul Urban Supervisor: Prof. Shaun Bangay Honours Project 2001

2. Problem Statement Traditional keyframing is inappropriate for animating realistic creatures in virtual environments, because it is Specified laboriously at a low level Strictly scripted, unvarying Often physically unrealistic Divided into sequences which don’t splice smoothly

3. Aim Our aim is to create virtual creatures that Are self-animating Exhibit physically realistic motion Have unscripted behaviour Are responsive to their unpredictable environment

4. The Solution: Animats Our approach is to construct complete artificial animals (animats). We draw upon theory and results from Artificial Life Physically Based Modelling Autonomous Mobile Robots

5. Anatomy of an Animat Dynamical model point-masses, springs, joints Sensors speed, food Actuators springs, joints Control mechanism finite state machine

6. Theory: Dynamical model The body and the environment are both modelled as a dynamical (mechanical) system A dynamics engine Animates the body and environment according to Newtonian mechanics Operates in (or near) real-time

7. Theory: Sensors Simulation Sensor Control mechanism Simulation data about creature body and environment Sensor activation level [0..1] Processing

8. Theory: Actuators Simulation Actuator Command to update some parameter in the simulated body Actuator activation level [0..1] Minimal processing Control mechanism

9. Theory: Control Mechanism Actuators Activation levels Sensors Control mechanism Solve the “action selection” problem In this project, FSMs are used

10. Design Overview Dynamics engine Roobot creature –Experiment to evolve hopping motion Jellyfish creature –Underwater environment Quadruped creature

11. Design: Dynamics engine No dynamics engine existed in greatdane Design criteria: –Conceptually simple –Applicable to a large variety of systems –Easily extendable –Computationally inexpensive

12. Design: Dynamics engine Object oriented decomposition Major abstract classes: –PointMass (single mass particle) –Force (applies force to several objects) –DiscreteEvent (detects and handles short-lived events) –Integrator (advances a system through time according physical laws)

13. Design: Roobot Springs Point masses Floor Torques Angular joints Gravity

14. Design: Roobot: Control Phases in the hopping motion corresponds to states in a FSM Transitions triggered by sensor values Different feedback algorithm for each state

15. Problem: Stable Hopping The roobot is dynamically unstable There are (14) parameters in the control FSM Values for stable hopping are unknown Parameters interact unpredictably “Fitness landscape” is unknown

16. Design: Hop Evolution Experiment Genetic algorithm is used Search for optimal sets of parameters Keep the best set so far Generate new sets through mutation Evaluate according to a fitness criterion (time till falling + distance travelled) Select if it beats the old best, replace old best

17. Design: Jellyfish Point masses Springs Gravity Buoyancy Pulse force Steering force

18. Design: Jellyfish: Control Three behaviours –Actively swimming –Pulsing occasionally to maintain depth –Drifting (sinking) passively Steering towards food occurs every pulse Action selection mechanism switches between these as appropriate

19. Design: Underwater environment Simulated fluid medium Currents to suggest waves overhead Swaying seaweed Rising bubbles Falling rocks

20. Design: Quadruped Flat torso defined by 4 point masses and 6 supporting springs Four legs (various models attempted) Control mechanism was to be based on that used for the roobot

21. Implementation Overview Dynamics engine Roobot creature Jellyfish creature –Underwater environment Quadruped creature

22. Implementation: Dynamics engine Coded in Java Compiles to a shared library, links into greatdane applications A number of additional objects defined, including –PointMass: SpherePointMass –Force: Spring, joints, Gravity, fluids, Floor –DiscreteEvent: Floor –Integrator: RungeKuttaIntegrator

23. Implementation: Creatures Coded in Java Models built from point masses, springs, angular joints and torque (rotational) joints Strict use of Sensor and Actuator interfaces

24. Implementation: Roobot Telescoping leg Hip & hip joint Tail Head Foot & ankle joint

25. Implementation: Jellyfish Dome Tentacles Stages in the pulsing motion

26. Implementation: Underwater environment Rocks Bubbles Seaweed

27. Implementation: Quadruped Torso Legs Control spring(s) Quadruped with supporting springs

28. Quadruped Abandoned Three different leg designs were tried A 2-segment jointed leg model couldn’t stand – knee joints twisted A 1-segment jointed leg model flipped over onto its back A 1-segment leg model with supporting springs was too complex to control

29. Results Overview Dynamics engine Stable Hopping Roobots Jellyfish swimming in an underwater environment

30. Results: Dynamics engine Object oriented dynamics engine implemented Highly applicable to particle systems Some difficulty with jointed structures

31. Results: Stable Hopping Roobots Stable hopping motion was evolved after a few hundred generations Separate evolutions from same starting parameters yielded different motions

32. Results: Swimming jellyfish Several jellyfish swim in a simulated underwater environment Interesting, physically realistic motion is generated automatically

33. Observations Dynamic simulation automatically produces realistic motion The design process is complex –Dynamics knowledge is crucial –Lazy modelling is optimal

34. Conclusions Our “bottom-up” approach to creature modelling using animats is validated The design process is complicated Genetic algorithms can be used to generate motor controllers Our dynamics engine simulates particle systems well, but jointed structures are not well handled

35. Thank you! Question time…