A skeleton for a particle filter algorithm (ParticleFilter.java)
The binary of a sample solution (sample_solution.jar)
Tasks
Implement the missing parts of ParticleFilter.java (use confusion=0.1 for the resampling)
Experiment with the settings for noise, number of sensors and number of particles to see the influence on how fast the agent knows its position and how good the estimate is
Try out what happens if you do not add white noise in the resampling step (set the confusion parameter of the resampling function to 0.0)
Hand in
Your code
A few sentences about your observations and what you can conclude from them. How do the number of sensors, number of particles, noise parameters and the confusion parameter influence the accuracy of the position estimate? Why is that so?