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Sensor Actuator Network

Sensor Actuator Network. Michiel van de Panne Eugene Fiume. SIGGRAPH 93. stochastic synthesis of controllers. sensory based - no state information. non-linear network of weighted connections between a small number of binary sensors and actuators (muscles).

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Sensor Actuator Network

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  1. Sensor Actuator Network • Michiel van de Panne • Eugene Fiume SIGGRAPH 93

  2. stochastic synthesis of controllers sensory based - no state information

  3. non-linear network of weighted connections between a small number of binary sensors and actuators (muscles) internal delays - for dynamic properites determine parameters to get desired behavior generate and test further optimization to refine controllers

  4. planar dynamics in vertical plane proportional-erivative controllers for forces & torques binary sensor values rigid links

  5. need fast dynamics simulator creatures are free bodies in space external ground forces use stiff spring & dampers friction, wind, viscosity are used

  6. weighted connections in range -2:2 fully connected nodes # of hidden nodes usually = # sensor nodes

  7. time delay fires ‘1’ if weighted input is positive

  8. Phase 1: random generate & test evaluation metric ‘distance traveled’ for most examples can incorporate other terms average height not falling over tracking of a point-to-follow

  9. Phase 2: Fine tuning non-linear stochatic gradient ascent or simulated annealing

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