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NANOROBOTICS CONTROL DESIGN: A PRACTICAL APPROACH TUTORIAL A. Cavalcanti, R.A. Freitas Jr., L.C. Kretly CAN Center for Automation in Nanobiotech IMM Institute for Molecular Manufacturing UNICAMP University of Campinas ASME 28th Biennial Mechanisms and Robotics Conference ASME DETC - Salt Lake City, Utah, USA September 28 to October 2, 2004

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The new era of Nanotechnology is coming

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Fact What is Nanotechnology Nanotechnology Challenge Proposed Approach Virtual Environment Nanorobot Design Environment Sensing Competitive Nanorobotics Collective Nanorobotics Contributions Fact P r e s e n t a t i o n o u t l i n e :

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FACT

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1. WHAT IS NANOTECHNOLOGY ?

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2. NANOTECHNOLOGY CHALLENGE a. Main goal of nanotechnology at nanoscale: - development of molecular nanomachine & systems ? Possible applications: - Nanoassembly automation - Health and environmental care

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3. PROPOSED APPROACH a. Mobile nanorobot control design - Perform molecular assembly manipulation - Applied to Nanomedicine b. Nanorobot aims - Molecules transport, assembly and delivery - Control organ inlets nutritional levels (ranging from 20 to 80%) ? target* 50% c. The delivery positions - Represent organ inlets requiring proteins - Located in known positions d. Macro-transponder for positional location

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4. VIRTUAL ENVIRONMENT c. Human body: - simplified 3D workspace ? a lower computational effort - is valuable approach to study nanorobotics control behaviors for nanomedicine

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e. Kinetics assumptions: nanoworld dominated by - Friction, adhesion, and viscous forces are paramount - Gravitational forces are of little or no importance 4. VIRTUAL ENVIRONMENT

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5. NANOROBOT DESIGN b. Nanorobot navigation: - Uses plane surfaces (three fins total) - Propulsion by bi-directional propellers: two simultaneously counter-rotating screw drives - navigational acoustic sensors a. Nanoassembly Manipulation is taken into the nanorobot with robotic arm (telescoping manipulator)

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6. ENVIRONMENT SENSING

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6. ENVIRONMENT SENSING

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7. COMPETITIVE NANOROBOTICS 3D Simulation

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8. COLLECTIVE NANOROBOTICS 3D Simulation

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9. CONTRIBUTIONS b. Rapid Evaluation of Various Control Algorithms

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FACT

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Fig.1: Highest/lowest organ inlets nutritional levels Control Performance – Competitive Nanorobots Fig.2: Histogram Q. & A.

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Fig.3: Multi-robot cooperative reaction Fig.4: Histogram cooperative reaction Control Performance – Collective Nanorobotics Q. & A.

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Control Performance – Neural Motion Control Fig.5: Neural motion planning Fig.6:Nanorobot motion cost optimization Q. & A.

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