A Hybrid Path-Planning Strategy for Mobile Robots with Limited Sensor Capabilities

. 2019 Mar 1;19(5):1049. doi: 10.3390/s19051049

Algorithm 2: Hybrid navigation algorithm.

Require: Occupancy Grid

O G

, Robot current Pose X, Robot Desired Pose

X_{d}

γ

, fe
Ensure: Occupancy Grid

O G

X_{d}

1:
$r o u t e \leftarrow A S t a r S e a r c h (O G, X, X_{d})$
2:
if $r o u t e W a s F o u n d$ then
3:
$p a t h \leftarrow G e n e r a t e P a t h (O G, X, X_{d})$
4:
$P a t h F o u n d \leftarrow t r u e$
5:
$d_{o b s} \leftarrow d_{o b s A}$
6:
$A e s c a p e \leftarrow f a l s e$
7:
else
8:
$d_{o b s} \leftarrow d_{o b s T}$
9:
end if
10:
while $X \neq X_{d}$ do
11:
$X \leftarrow G e t R o b o t O d o m e t r y ()$
12:
$M \leftarrow G e t S e n s o r D a t a ()$
13:
$U p d a t e M a p (O G, M, X)$
14:
if $P a t h F o u n d$ then
15:
$\begin{matrix} if (m i n (M) \leq d_{o b s A} \land \neg (A e s c a p e)) \lor \\ (A e s c a p e \land m i n (M) \leq d_{o b s T}) \end{matrix}$ then
16:
$d_{o b s} \leftarrow d_{o b s T}$
17:
$A e s c a p e \leftarrow t r u e$
18:
else
19:
$d_{o b s} \leftarrow d_{o b s A}$
20:
$A e s c a p e \leftarrow f a l s e$
21:
end if
22:
$C o n t r o l l e r \leftarrow P a t h F o l l o w i n g C o n t r o l l e r$
23:
$X_{d} \leftarrow g e t C l o s e s t P a t h P p o i n t$
24:
end if
25:
$X_{d} \leftarrow T a n g e n t i a l E s c a p e (m i n (M), d_{o b s}, f e, γ)$
26:
$U \leftarrow C o n t r o l l e r (X, X_{d})$
27:
$s e n d C o n t r o l S i g n a l s$
28:
end while
29:
return $O G, X$