Method for characterizing the environment of a mobile device, producing a static space grid and/or a free space grid
A method for characterizing the environment of a mobile device, wherein, for each iteration at a time t, the following steps are implemented: S 10 ) Acquiring a plurality of distance measurements (z t ) in the environment by way of at least one sensor; S 20 ) Generating a pair (w t ) of occupancy grids at the time t−1 (OG t-1 ) and at the time (OG t ), each grid (OG t-1 , OG t ) fusing the distance measurements into a discretized spatial representation of the environment; S 30 ) Generating a static space grid at the time (SG t ), Or S 40 ) Generating a free space grid at the time (FG t ).
1 . A method for characterizing the environment of a mobile device, wherein, for each iteration at a time t, the following steps are implemented:
S 10 ) Acquiring a plurality of distance measurements (z t ) in the environment by way of at least one sensor;
S 20 ) Generating a pair (w t ) of occupancy grids at the time t−1(OG t-1 ) and at the time t(OG t ), each grid (OG t-1 , OG t ) fusing the distance measurements into a discretized spatial representation of the environment;
S 30 ) Generating a static space grid at the time (SG t ), each cell (SG t (i)) of the static space grid at the time t having a subsequent probability of said cell being occupied by a static tangible body at the time t (P(s t |w 1:t )), said subsequent probability P(s t |w 1:t ) being computed for each cell (SG t (i) by way of a binary Bayesian filter from:
the subsequent probability of said cell being occupied by a static tangible body at the time −1 (P(s t-1 |w 1:t−1 )), said subsequent probability of said cell being occupied by a static tangible body at the time t−1 (P(s t-1 |w 1:t−1 )) being injected directly at input of the binary Bayesian filter;
what is referred to as a static prediction model corresponding to a probability of the cell being occupied by a static tangible body at the time t as a function of the state of the cell at the time t−1 (P(s t |s t-1 )); and
what is referred to as a static inverse model at the time t(P(s t |w t )) corresponding to a probability of knowing that the cell is occupied by a static tangible body at the time t from the pair of occupancy grids at the time t−1 and at the time t;
and/or
S 40 ) Generating a free space grid at the time t (FG t ), each cell (FG t (i)) of the free space grid at the time t having a subsequent probability of said cell being free at the time t P(f t |w 1:t )), said subsequent probability being computed for each cell by way of a binary Bayesian filter from:
the subsequent probability of said cell being free at the time t−1 (P(f t-1 |w 1:t−1 )), said subsequent probability of said cell being free at the time t−1 (P(f t-1 |w 1:t−1 )) being injected directly at input of the binary Bayesian filter;
what is referred to as a free prediction model corresponding to a probability of the cell being free at the time t as a function of the state of the cell at the time t−1 (P(f t |f t-1 )); and
what is referred to as a free inverse model at the time t (P(f t (w t )) corresponding to a probability of knowing that the cell is free at the time t from the pair of occupancy grids at the time t−1 and at the time t.
2 . The method according to claim 1 , wherein step S 30 ) of generating a static space grid and step S 40 ) of generating a free space grid are implemented concomitantly.
3 . The method according to claim 2 , comprising a step S 50 ) of generating a combined grid (CG t ) resulting from the combination of the static space grid (SG t ) and the free space grid (FG t ).
4 . The method according to claim 3 , wherein each cell i of the combined grid (CG t ) is computed by way of the following Bayesian fusion:
CG
t
(
i
)
=
Δ
F
(
SG
t
(
i
)
,
1
-
FG
t
(
i
)
)
wherein F(,) is the Bayesian fusion function, CG t (i) corresponds to a cell i of the combined grid at the time t, SG t (i) corresponds to a cell i of the static space grid at the time t, and FG t (i) corresponds to a cell i of the free space grid at the time t, And according to the value of CG t (i):
if CG t (i)>½, the cell i is probably static given the sequence of pairs of occupancy grids (w 1:t )
if CG t (i)<½, the cell is probably free,
if CG t (i)=½, the cell is neither free nor static.
5 . The method according to claim 1 , wherein:
the subsequent probability of the cell being occupied by a static tangible body at the time t (P(s t |w 1:t )) and the static inverse model at the time t (P(s t |w t )) are approximated by values belonging to a set of finite cardinality, the values being identified respectively by a probability index n(s t |w 1:t ) and by a static inverse model index n(s t |w t );
the subsequent probability of the cell being free at the time t (P(f t |w 1:t )) and the free inverse model at the time t (P(f t |w t )) are approximated by values belonging to a set of finite cardinality, the values being identified respectively by a probability index n(f t |w 1:t ) and by a free inverse model index n(f t |w t ).
6 . The method according to claim 5 , wherein the static inverse model index n(s t |w t ) is computed as follows:
n
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s
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❘
w
t
)
=
{
g
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w
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>
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if
n
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and
n
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otherwise
the function g(w t ) returning a positive value, n(o i,t−1 |z t-1 ) corresponding to the occupancy index of the cell i of the occupancy grid OG t-1 at the time t−1, and n(o i,t |z t ) corresponding to the occupancy index of the cell i of the occupancy grid OG t at the time t.
7 . The method according to claim 5 , wherein the free inverse model index n(f t |w t ) is computed as follows:
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=
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if
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<
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otherwise
and n(o i,t |z t ) corresponding to the occupancy index of the cell i of the occupancy grid OG t at the time t, the function h(w t ) returning a positive value.
8 . The method according to claim 6 , wherein the positive value of the function g(w t ) and the positive value of the function h(w t ) are constant values (β SG , β FG ).
9 . The method according to claim 6 , wherein the positive value returned by the function g(w t ) is equal to max(n(o i,t−1 |z t-1 ), n(o i,t |z t ).
10 . The method according to claim 7 , wherein the positive value returned by the function h(w t ) is equal to −n(o i,t |z t ).
11 . The method according to claim 5 , wherein the free inverse model index n(f t |w t ) is computed as follows:
n
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f
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❘
w
t
)
=
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max
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-
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if
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otherwise
n(o i,t |z t ) corresponding to the occupancy index of the cell i of the occupancy grid OG t at the time t, and n(o i,t−1 |z t-1 ) corresponding to the occupancy index of the cell i of the occupancy grid OG t-1 at the time t−1.
12 . The method according to claim 5 , wherein step S 30 ) of generating a static space grid and step S 40 ) of generating a free space grid are implemented concomitantly, and comprising a step S 50 ) of generating a combined grid (CG_t) resulting from the combination of the static space grid (SG_t) and the free space grid (FG_t),
wherein the index n(s t |w 1:t−1 ) corresponding to the prediction component of the binary Bayesian filter of the static space grid is obtained using a look-up table comprising a finite set of probability indices, and the filtered index n(s t |w 1:t ) is obtained by adding integer probability indices, and
wherein the index n(f t |w 1:t−1 ) corresponding to the prediction component of the binary Bayesian filter of the free space grid is obtained using a look-up table comprising a finite set of probability indices, and the filtered index n(f t |w 1:t ) is obtained by adding integer probability indices.
13 . The method according to claim 5 , wherein each cell i of the combined grid (CG t ) is computed by way of the following Bayesian fusion:
CG
t
(
i
)
=
Δ
SG
t
(
i
)
,
1
-
FG
t
(
i
)
CG t (i) corresponds to a cell i of the combined grid at the time t, SG t (i) corresponds to a cell i of the static space grid at the time t, and FG t (i) corresponds to a cell i of the free space grid at the time t,
and according to the value of CG t (i):
if CG t (i)>0 the cell i is probably static given the sequence of pairs of occupancy grids (w 1:t )
if CG t (i)<0, the cell is probably free,
if CG t (i)=0, the cell is neither free nor static.
14 . The method for avoiding a tangible body moving around a mobile device, implementing the method according to claim 1 to characterize the environment of a mobile device, and in that it sends a command to an actuator of the mobile device in order to avoid said tangible body.
15 . A device for characterizing the environment of a mobile device, the characterization device comprising:
at least one input port for receiving a plurality of signals representative of a time series of distance measurements from one or more distance sensors, and
a data processor configured to receive said signals at input and to generate a free space grid or a static space grid from said signals by applying a method according to claim 1 .