Adaptive Obstacle Detection for Mobile Robots in Urban Environments Using Downward-Looking 2D LiDAR

. 2018 May 29;18(6):1749. doi: 10.3390/s18061749

Algorithm 2: Extract the vector of scanned road surface.

INPUT: road line segments sets

R L_{i}

ϑ_{i t}

and

t_{i}

.
OUTPUT:

{\vec{V}}_{t_{i}}

Θ = \emptyset (s e t Θ i n i t a l v a l u e i s n u l l s e t)

i f t_{i} = t_{0}

t^{*} = \max (l e n_{i t})

{\vec{V}}_{t_{i}} = {\vec{v}}_{t^{*}}

04 else
05

f o r a l l l_{i t} i n R L_{i}

i f ϑ_{i t} < ϕ_{\max} a n d l e n_{i t} > L_{\min}

Θ = Θ \cup {S p_{i t}^{L}, E p_{i t}^{L}}

08 end
09 end
10

G e t \hat{a}, \hat{b} u s i n g t h e l e a s t s q u a r e f r o m Θ

c h o o s e t w o e n d p o i n t s p_{1}^{L}, p_{2}^{L} f r o m l i n e : y = \hat{a} x + \hat{b}

C o n v e r t p_{1}^{L}, p_{2}^{L} t o F_{W} c o m b i n i n g (3), a n d g e t p_{1}^{W}, p_{2}^{W}

{\vec{V}}_{t_{i}} = p_{2}^{W} - p_{1}^{W}

14 end
return

{\vec{V}}_{t_{i}}