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Component based, hardware-software system for fuzzy controlling of automated vehicles. László Siroki 5 th year comp. sci. Tivadar Pápai 5 th year comp. sci. Attila Geresdi 5 th physicist Supervisor: Dr. László T. Kóczy, TMIT. The motivation. Contest in Kiskunhalas, 2006
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Component based,hardware-software system for fuzzy controlling of automated vehicles László Siroki 5th year comp. sci. Tivadar Pápai 5th year comp. sci. Attila Geresdi 5th physicist Supervisor: Dr. László T. Kóczy, TMIT
The motivation • Contest in Kiskunhalas, 2006 • Task: build a mars rover model from simple elements • The mission: • find a metal plate hidden under the sandy surface • take sand sample over the plate • take this back to the base • dodge the obstacles • Difficulties • every user command was delayed by 30s • Orientation by the photos of a „satellite” (web camera)
Finish line We are behind the draught screen Base
Construction • Caterpillar model vehicle • Own motor driver electronics • Controlling unit: „mitmót” (with TinyOS system) • Motor controlling, sensor handling, radio communication • Sensors: • Metal detector • Collision detector • Outputs: • Trier • (LEDs)
GUI Rover configuration View, controler World model Caterpillar model Caterpillar controller Caterpillar controlling TinyOS message handling View, controler Position detector objects Web camera locator Web camera handling Position calculation LED detection Software architecture • Component-based, replaceable elements, expandable • Implementation: C#.NET 2.0
TB,E kB kE TC,E TB,C kC TC,P TP,DP d kDP kP d d d Position-determination • Web camera at a fixed location • LEDs • Pattern is important • Image processing • Detection of LEDs • Calculation of 3D transformation • Web camera calibration
The controller • Purpose: to follow a piece-wise linear path • Difficulties: • The behavior of the rover is non-linear • We get the position of the rover delayed • The delay can oscillate • The system is non-linear
pseudo target end angular deviation start mars rover The simpliest solution: fuzzy controller • Inputs: • Angular deviation • Angular velocity • Outputs: • Average of the caterpillar-tracks’ signals • and their difference
User interface • Configuration • Sematic map • Path creation • Manual control • Buttons • Joystick
Path planning Reduced to a physics problem Springs with charged ends Repelling stones Finding the state with minimal energy by Monte-Carlo method Future plans - 1
Future plans - 2 • Simulator • Necessity • Making development faster (developing without a vehicle) • Optimization of the controller • At the next year’s contest satellite picture will be available every 1s, between these intervals we could estimate the vehicle’s position • Implementation • MLP network (using its universal approximator property)