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Biomimetic Design

Biomimetic Design. James Tacey , Aditi Shinde. Biomimetic Systems. Neural Networks Biological Redundancy Self-Repair Artificial Intelligence. Neural Networks. Groups of connected nodes or neurons Capable of finding non-linear patterns Highly adaptable to new inputs stimuli

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Biomimetic Design

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  1. Biomimetic Design James Tacey, AditiShinde

  2. BiomimeticSystems • Neural Networks • Biological Redundancy • Self-Repair • Artificial Intelligence

  3. Neural Networks • Groups of connected nodes or neurons • Capable of finding non-linear patterns • Highly adaptable to new inputs stimuli • Excellent choice for control systems of biomimetic locomotion

  4. Biological Redundancy • Many animals have redundant systems • Systems allow continued functionality after a limb or other system is damaged • Redundancy prevents single point-of-failure in the system • Adaptation to a robotics allows for more longer and more reliable functionality

  5. Self-Repair • Animals are capable of healing and repairing damage done • Repair algorithms and self-repairing materials • Allows robot to become more durable and capable of lasting in more harsh environments

  6. Artificial Intelligence • Still in early stages of research • Robots can be ‘taught’ very simple tasks • Would allow robots to adapt • Wide variety of application in robotics, ability to ‘learn’ variety of tasks

  7. Artificial Muscles • Shape Memory Effects • Electroactive Polymers • Chemical Muscles

  8. Shape Memory Effects • Use of materials that ‘remember’ shapes • Material is ‘taught’ a shape • Temperature controlled ‘muscle’ • Slow but more durable ‘muscle’ for robotic applications

  9. Electroactive Polymers • Polymers that change shape • Electrically stimulated • Highly pliable materials with a wide-variety of applications

  10. Chemical Muscles • Similar to biological muscles • Non-combustible chemical reaction drives cylinder • Higher energy density than electricity

  11. Evolutionary Robotics • Hardware and software co-evolution • Use of genetic algorithms and neural networks • Allows more adaptive design • Requires less trial and error • Effective for developing robotic gaits

  12. Robotic lobster

  13. Lamprey-based undulatory vehicle

  14. CWRU’s Robot V

  15. CWRU’s Cricket microrobot

  16. Standford’siSprawl

  17. Fraunhofer Institute’s Scorpion

  18. Mesoscale robot quadruped

  19. Snake robot S7

  20. RoboTuna

  21. VCUUV

  22. Georgia Tech’s Entomopter

  23. Neural oscillator control network for Rodney

  24. Oct-1b

  25. Sony quadruped robot

  26. Koharo

  27. Random morphology robot

  28. Self-modeling robot

  29. Golem

  30. Genobots

  31. CCSLs Nonaped

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