Here is an implementation of particle filter in Python using numpy:
main.py920 chars28 lines
In this implementation, num_particles
is the number of particles, initial_pose
is the initial pose of the robot (x, y, theta), z
is a list of sensor measurements, motion_model
is a function that predicts particle motion, sensor_model
is a function that computes particle weights based on sensor measurements, and map
is a representation of the environment.
The particle_filter
function initializes num_particles
particles, iterates over the sensor measurements, predicts particle motion using motion_model
, computes particle weights using sensor_model
, normalizes the weights, resamples particles based on the weights, and finally computes the estimated position as the mean of particles.
Note that motion_model
and sensor_model
are functions that you need to define based on your specific application.
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