Localization/particle filter

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The main files are:


Due to difficulties in the implementation, changes were made to the dictated theoretical outline of the implementation.

  • Since the hovercraft floats on a cushion of air, gravity effects the force applied to each thruster.
    • As a result, if we include the forces in the motion model update we have particles that travel away from the force of gravity.
    • This makes our particle cloud constantly drift away from the true pose.
    • Attempts were made to offset the influence of gravity in the calculations, but the effect of gravity is different throughout the room.
    • We could not get consistent results with this method.
  • We therefore do not include the forces in the motion model update.
    • We realize that this violates the theoretical objective of closed-loop control and estimation.
    • However, we have designed the measurement model to compensate for this violation by making it more robust and exact.
    • Also, we increase the amount of system or motion noise in our motion model to compensate for the effect of the forces.
      • Practically speaking, this is a Hovercraft that can't move that far in 50,100 or even 250 ms intervals which is the rate of the filters.
      • Hence, using sufficient random noise gives a good particle cloud dispersion and compensates for the neglected forces.
    • In practice, this method produces good results in pose estimation, and satisfactory results in Hovercraft control.
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