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configuration space of the robot, we naturally model a trajectory deformation pro-
cess as a mapping of two real variables
s
and
can
be considered as time (or more generally as an increasing function of time), while
s
is the abscissa along each trajectory.
The chapter is organized as follows. Section 17.2 defines trajectory deformation
as an infinite-dimensional dynamic control system the state of which is a trajec-
tory. In Section 17.3, we describe an iterative algorithm controlling the deformation
process to make an optimization criterion decrease. In Section 17.4, the trajectory
deformation algorithm is applied to mobile robot Hilare 2 towing a trailer. In Section
17.5, the method is extended to perform docking for nonholonomic robots.
τ
into the configuration space.
τ
17.2
Nonholonomic Trajectory Deformation as a Dynamic
Control System
A trajectory for a robotic system is usually represented by a mapping from an inter-
val of
into the configuration space of the system. In this section, we introduce the
notion of trajectory deformation as a mapping from an interval of
R
into the set of
trajectories. Equivalently, a trajectory deformation is a mapping from two intervals
into the configuration space as explained later in this section.
R
17.2.1
Admissible Trajectories
<
A nonholonomic system of dimension
n
is characterized by a set of
k
n
vector
n
is the configuration of the system. For
each configuration
q
, the set admissible velocities of the system is the set of linear
combinations of the
X
i
(
q
). A trajectory
q
(
s
) is a smooth curve in the configuration
space defined over an interval [0
,...,
∈ C
R
fields
X
1
(
q
)
X
k
(
q
),where
q
=
S
]. A trajectory is said to be admissible if and
only if there exists a k-dimensional smooth vector valued mapping
u
=(
u
1
,
,...,
u
k
)
defined over [0
,
S
] and such that:
k
i
=1
u
i
(
s
)
X
i
(
q
(
s
))
S
]
q
(
s
)=
∀∈
,
[0
(17.1)
where from now on,
denotes the derivative with respect to
s
.
17.2.2
Admissible Trajectory Deformation
2
We call trajectory deformation a mapping from a subset [0
,
S
]
×
[0
,
∞
) of
R
to the
configuration space of the system:
(
s
,
τ
)
→
q
(
s
,
τ
)
.
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