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The following papers are available by anonymous ftp to imag.fr (129.88.32.1)
in the directory /pub/LIFIA.

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 Thierry Fraichard		                   Thierry.Fraichard@imag.fr
 LIFIA-INRIA Rhone-Alpes                           Tel : +33 76.57.46.41 (job)
 46, av. Felix Viallet                                   +33 76.87.21.27 (home)
 38031 Grenoble Cedex 1, France                    Fax : +33 76.57.46.02
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TITLE		:Kinodynamic Planning in a Structured 
		:and Time-Varying Workspace
AUTHOR(S)	:Th. Fraichard and C. Laugier
REFERENCE	:Lecture Notes in Computer Science 708, Springer-Verlag
LANGUAGE	:English
LENGTH		:19 pages
DATE		:1993
KEYWORDS	:Robotics, Motion Planning, Non-Holonomy, Dynamics, 
		:Moving Obstacles
FILE NAME	:fraichard.lncs93.e.ps.Z
Author E-mail	:tf@cosmos.imag.fr
Related Files	:
ABSTRACT	:This paper deals with a kinodynamic trajectory planning
problem that we call the `highway problem'. It consists in planning a
time-optimal trajectory for a robot which is travelling in a structured
workspace amidst moving obstacles and which is subject to constraints on its
velocity and acceleration.  By structured workspace, we mean that there are
lanes within which the robot is able to move.  A lane is characterized by its
`spine', i.e. a one-dimensional curve.  The robot has to follow a
predetermined lane but it may also shift from its lane to an adjacent one.
This paper presents an efficient method which determines an approximate
time-optimal solution to the highway problem. The approach consists in
discretizing time and selecting the acceleration applied to the robot among a
discrete set.  These hypotheses make it possible to define a grid in the
robot's state-time space, i.e. the robot's state (or phase) space augmented of
the time dimension.  This grid is then searched in order to find a solution.
Accordingly trajectory planning is reduced to graph search.
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TITLE		:Dynamic Trajectory Planning, Path-Velocity Decomposition
		:and Adjacent Paths
AUTHOR(S)	:Th. Fraichard and C. Laugier
REFERENCE	:Proc. of the Int. Joint Conf. on Artificial Intelligence
		:Volume 2, pp.1592-1597
LANGUAGE	:English
LENGTH		:6 pages
DATE		:August-September 1993
KEYWORDS	:Robotics, Motion Planning, Non-Holonomy, Dynamics, 
		:Moving Obstacles
FILE NAME	:fraichard.ijcai93.e.ps.Z
Author E-mail	:tf@cosmos.imag.fr
Related Files	:
ABSTRACT	:This paper addresses motion planning for a robot A moving in
a dynamic workspace. A is subject both to kinematic and dynamic constraints.
The approach presented is an extension to the `path-velocityd decomposition'
[Kant & Zucker 1986] which introduce the concept of adjacent paths: a set of
adjacent paths, one of which leading A to its goal, are computed. These paths
are collision-free with the stationary obstacles and respect A's kinematic
constraints.  Then, knowing that A is able to shift from one path to an
adjacent one freely, the motion of A along and between these paths is computed
so as to avoid any collision with the moving obstacles while respecting A's
dynamic constraints.
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TITLE		:Dynamic Trajectory Planning with Dynamic Constraints: 
		:a `State-Time Space' Approach
AUTHOR(S)	:Th. Fraichard
REFERENCE	:Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots 
		: and Systems. pp. 1393-1400
LANGUAGE	:English
LENGTH		:8 pages
DATE		:July 1993
KEYWORDS	:Robotics, Motion Planning, Non-Holonomy, Dynamics
		:Moving Obstacles
FILE NAME	:fraichard.iros93.e.ps.Z
Author E-mail	:tf@cosmos.imag.fr
Related Files	:
ABSTRACT	:This paper addresses `dynamic trajectory planning' which
is defined as trajectory planning for a robot subject to dynamic constraints
and moving in a dynamic workspace, i.e. with moving obstacles.  To begin with,
we propose the novel concept of `state-time space' as a tool to formulate
dynamic trajectory planning problems.  The state-time space of a robot is its
state space augmented of the time dimension.  It permits to study the
different aspects of dynamic trajectory planning in a unified way.  Thus the
constraints imposed by both the moving obstacles and the dynamic constraints
can be represented by static forbidden regions of state-time space.  Besides a
trajectory maps to a curve in state-time space hence dynamic trajectory
planning simply consists in finding a curve in state-time space.  Then we
apply this new concept in order to determine a time-optimal trajectory for a
car-like robot subject to dynamic constraints and moving along a given path on
a dynamic planar workspace.
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