A Self Balancing Robot

Transcript

How to Design, Simulate, and Manufacture a Self-Balancing Robot David Truyens Application Engineer Twitter: @davidtruyens Join the conversation #AU2015 Key learning objectives At the end of this class, you will be able to:  Learn how to simulate a self-balancing robot within Inventor DS  Learn how to use this technology to solve real-world challenges  Discover what the speaker has tried and what didn't work  Discover the future of making machines Why? Why you shouldn’t …  Uncountable hours  Money  Less sleep  Headache  Relationship Why you should!  Controllers are everywhere!  Everything is possible these days  FOMT Full Motion Dynamics Flanders Make Balanduino / TKJ Electronics Arduino - Massimo Banzi Gadgets Hibbot Ampelmann Real stuff Space and automotive Why you should A self balancing robot Control Software Firmware CAD Hardware Virtual Physical Theory A self balancing robot Firmware Virtual Physical Garage version Firmware Virtual Physical Garage Version  Open Pandora’s box: Garage Version 9 DoF MPU?  Gyro (electronical) = angular velocity Very accurate! No angle!!  Accelerometer = gravity and other accelerations Direct angle Lot’s of noise…  Compass = North direction in an XYZ vector Gravity independent Slow and not accurate PID Controller I*  P proportional  I integral  D derivative 𝐷 ∗ 𝜃𝑏 𝑏𝑎𝑙𝑎𝑛𝑐𝑒 𝑒𝑟𝑟𝑜𝑟 𝑷 ∗ 𝜃𝑏 Master Slave - PID Controller 𝜃𝑇𝑎𝑟𝑔𝑒𝑡 = 𝑃𝑝𝑜𝑠 ∗ ∆𝑑 − 𝐷𝑝𝑜𝑠 ∗ 𝑣 Master-slave controller 0 + - Cpos 𝑑 𝑑 + - Cangle 𝜃 𝜃 Kalman Marvin Next challenge…. Gearboxes… Master-slave fuzzy-logic controller 0 + - Cpos 𝑑 𝑑 + - Cangle Marvin 𝜃 𝜃 Kalman 𝑃𝑎𝑛𝑔𝑙𝑒 𝐷𝑎𝑛𝑔𝑙𝑒 𝑃𝑎𝑛𝑔𝑙𝑒 𝐷𝑎𝑛𝑔𝑙𝑒 𝑃𝑝𝑜𝑠 𝐷𝑝𝑜𝑠 𝐾𝑎𝑙𝑚𝑎𝑛 Marvin Launch Pad Garage Version Advantages Disadvantages • Bottom up – step by step • Trial and error, error, error • Quick results • Not possible for large scale • Not much theoretical background needed • Fun / educational projects • Limited in complexity Classical approach Mathlab – Simulink - Simmechanics Firmware Virtual Physical Classical approach Advantages Disadvantages • Industry standard • Broken workflow in Inventor • Lots of options • Complicated • Option to link cad data • Easy to make mistakes • No validation Co-Simulation approach Mathlab – Cosimate - Inventor Firmware Virtual Physical Co-Simulation approach Co-Simulation approach Advantages • Connected worfklows with Inventor and Mathlab Disadvantages • Slow • Complicated • Industry standard • Easy to make mistakes • Collaborate with multiple • No validation users (Cosimate) Virtual validation workflow Firmware Virtual Physical Virtual validation workflow Virtual validation workflow Advantages Disadvantages • Fully integrated in Inventor • Quite hidden • Validation of the control • Not easy to program software • Lots of potential using iLogic • Strange things when programming Conclusions  Lots of way’s to work  Make your hands dirty Future  Collaborate with Autodesk on Smart Machines  Create my own pcb with Circuits IO  Make the next Marvin Next generation Open call Inventor in Motion project on github Contact me!     Mail: [email protected] Twitter: @davidtruyens Github: https://github.com/DavidTruyens Fusion model: http://a360.co/1XD0Xt4 Autodesk is a registered trademark of Autodesk, Inc., and/or its subsidiaries and/or affiliates in the USA and/or other countries. All other brand names, product names, or trademarks belong to their respective holders. Autodesk reserves the right to alter product and services offerings, and specifications and pricing at any time without notice, and is not responsible for typographical or graphical errors that may appear in this document. © 2015 Autodesk, Inc. All rights reserved.