Course project that implements the Viterbi and Forward-Backward algorithms for tracking a robot's location on a grid.
File rover.py contains functions for generating the initial distribution, the transition probabilities given a current hidden state, and the
observation probabilities given a current hidden state.
Files test.txt and test_missing.txt contain data. The first three columns correspond to the hidden states, and the last two columns correspond to the observations.
A visualization tool is provided by graphics.py, which can be turned on by setting enable_graphics to True in inference.py.
Run inference.py to observe results.