Hidden-Markov-Model-

Resolving and predicting future steps taken by a Robot using Hidden Markov Model to model the unobservable/hidden paths(states). In this work, we propose a strategy based on Hidden Markov Model for simulating an agent or a robot placed in a random location in an unknown environment. We receive information from the robot through the sensors. The robot constructs the map of an unknown environment(warehouse) while keeping track of its current location.

Reference: https://dtransposed.github.io/blog/Robot-Localization.html