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Documentation

Artificial Potential Field Concept

Target Potential Field

  • Force beetween Target and Agent
  • constants:
  1. damping factor
  2. gain (to accelerate reaching to the target)
  3. target detecting range

Object

  1. Agent
  2. Target
  3. TargetPotentialField

Code Architecture

  1. Each Object will return the valued calculated
  2. The main.py will contain the state of variables to draw the graph

Itung Manual

Obstacle Potential Field

Drone 1 position = 0,0,0 Drone 1 mass = 1 Target 1 position = 9,9,9 gain = 1 target detecting range = 1 damping factor = 1

-- Iterasi 1 -- Obstacle Potential Force = ((1/15.5884572681 - 1/1)*1/(15.5884572681^2)

1*(15.5884572681 - 1)) * (0.57735026919, ..., ...)

Target Potential Field

Drone 1 position = 0,0,0 Drone 1 mass = 1 Target 1 position = 9,9,9 gain = 1 target detecting range = 1 damping factor = 1

-- Iterasi 1 -- Attractive Force = -(1*(-9,-9,-9)/9akar3) = (0.57735026919, ..., ...) Target Force = (0.57735026919, ..., ...) - 1 ((0,0,0)-(0,0,0)) = (0.57735026919, ..., ...) New Velocity = (0.57735026919, ..., ...) New Position = (0.57735026919, ..., ...)

-- Iterasi 2 -- Attractive Force = -(1*(-8.423,-8.423,-8.423)/-8.423akar3) = (0.57735026919, ..., ...) Target Force = (0.57735026919, ..., ...) - 1 ((0.57735026919, ..., ...)-(0,0,0)) = (0, 0, 0) New Velocity = (0.57735026919, ..., ...) New Position = (1.15470053838, 1.15470053838, 1.15470053838)