Ćwiczenia mają na celu implementację mechanizmu particle filtering lub filtru Kalmana do estymacji położenia użytkownika mobilnego w pomieszczeniu, przy wykorzystaniu symulowanego środowiska z trzema beaconami.

Bazujemy na repo: Trilateracja

Imagine you build a a robot that will serve as an ambien assistant. It has a map of a building where it operates, but it needs to localize itself on the map.

Fortunately, there are beacon stations planted around the building, which have known location. They send their locations in messages that the robot can receive. Additionally, the robot can measure the strength of the signal called RSSI. What is more, it knows that the dependency between the RSSI and distance to the beacon station is expressed with the following equation:

Where A is a known beacon station power also encapsulated in the message. The n is a constant that characterizes the building and is also encapsulated in the message.

Write a program to determine the robot location.