Particle Smoother-Based Landmark Mapping for the SLAM Method of an Indoor Mobile Robot with a Non-Gaussian Detection Model

Algorithm 1

SLAM based on particle smoother for landmark mapping and particle filter for self-localization.

1: Initialize robot particles

2: for to do

3:  Update particles with the motion model:

4: end for

5: if tag is detected then

6:  if tag is detected for the first time then

7:   Initialize tag particles

8:   Store in

9:  else

10:   for From to do

11:    Obtain based on with a Gaussian random value

12:    Update on the basis of the likelihood function

13:    Store in

14:   end for

15:  end if

16:  for From to do

17:   Draw with probability

18:   Add to

19:  end for

20:  

21:  for From to do

22:   

23:  end for

24:  Update based on and

25:  for From to do

26:   Update on the basis of the likelihood function

27:  end for

28: end if

29: for to do

30:  Draw with probability

31:  Add to

32: end for

33: 

34: return ,