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C ([0
k )
v
,
S ] , R
C ([0
n )
q
,
S ]
, R
Current
trajectory
n
η
R
0
Controller
senso r s
Fig. 17.1 A trajectory deformation process can be modelled as a dynamic control system
of time τ. At each time, the state is a feasible trajectory q , the input is a pair (η 0 , v )that
uniquely defines the time derivative of the state. The trajectory deformation algorithm we
describe in this chapter can be considered as a closed-loop controller that computes the input
of the dynamic control system with respect to the current trajectory and a task to achieve, for
instance avoiding obstacles, based on perceptual data
For each value of
0) is called the initial
trajectory . In order to keep notation light and intuitive, we use the same nota-
tion q to denote configurations, trajectories and trajectory deformations. We are
interested in deformations q ( s
τ
, s
q ( s
, τ
) is a trajectory. s
q ( s
,
) composed of only admissible trajectories. Such
deformations satisfy the following constraint: there exists a k -dimensional vec-
tor valued smooth mapping u =( u 1 ,...,
, τ
u k ) defined over [0
,
S ]
×
[0
,
) such that
, τ
,
×
,
( s
)
[0
S ]
[0
)
k
i =1 u i ( s , τ) X i ( q ( s , τ)) .
q
s ( s
, τ
)=
(17.2)
, τ
, τ
For each value of
).The
above equation simply expresses constraint (17.1) for each trajectory of the defor-
mation. As well as a trajectory is uniquely defined by the initial configuration and
the input function, a trajectory deformation is uniquely defined by the initial config-
uration q (0
τ
, s
u ( s
) is the input function of trajectory s
q ( s
).
By differentiating (17.2), we get a relation between the input variation u
∂τ
, τ
) of each trajectory and by input functions u i ( s
, τ
and the infinitesimal trajectory deformation when the deformation parameter
τ
increases:
)
2 q
k
i =1
u i
∂τ
)
X i
))
q
∂τ
( s
, τ
)=
( s
, τ
) X i ( q ( s
, τ
)) + u i ( s
, τ
q ( q ( s
, τ
( s
, τ
s
∂τ
We call respectively input perturbations and direction of deformation the following
vector valued functions:
 
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