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MOTION PLANNING FOR MOBILE ROBOTS IN DYNAMIC
ENVIRONMENTS
Jing Ren, Kenneth.A. McIsaac and Xishi Huang
University of Western Ontario
London ON, Canada N6G 1H1
Keywords:
Potential field, multi-robot motion planning, stability, dynamic environment.
Abstract:
In this paper, we present a motion planning technique for a multi-robot team in a complex dynamic environ-
ment. We define a cell-based navigation control law that can guide the robot team through the environment
while avoiding collisions with both static and dynamic obstacles and other team members. To illustrate our
techniques, we consider a robot team motion planning problem in a complex “maze” with obstacles of arbi-
trary shape. First, we assign potential values to a set of landmarks based on their shortest distance to the goal,
and then we use a spline function to generate a potential field for the entire workspace, which is inherently
free of undesired local minima. Simulation results show that robots can successfully transport materials along
an optimal and collision-free path and reach the goal in a complex and dynamic maze environment. Finally
we prove the derived control law is stable in all times.
1 INTRODUCTION
A central issue in mobile robotics is navigation strat-
egy. Potential field approaches are widely used for
motion planning in mobile robotics because of their
simplicity and elegance. In Koditschek’s basic for-
mulation (Koditschek 1989), a scalar field compris-
ing artificial “hills” (representing obstacles, or other
robots) and “valleys” (attractive positions) in the
robot’s world map lead naturally to a stable path to-
wards a “low-energy” goal position. Extensive work
has been done for single robot navigation. But much
less investigation is devoted to a team navigation in
the dynamic and complex environment.
Although single robots can play an important role
in many areas, the use of multi-robot teams has a
number of potential advantages over single robot sys-
tems. A group of robots working together can accom-
plish the task of a complex, purpose-built system in
a fraction of the time, and the built-in redundancy of
having many team members leads to a more robust-
ness and fault tolerance.
Dynamic environment is a recurring challenge in
motion planning. Robots providing services in sewer
systems, office buildings, supermarkets or even pri-
vate homes must be able to adapt on-line to un-
predictable dynamic obstacles, such as people going
about their own business. For a single robot, Espos-
ito (Esposito 2002) proposed a technique to treat un-
predictable obstacles as dynamic constraints that limit
the choices of feasible trajectories. In this paper, we
modified and extended this technique to a robot team.
2 PROBLEM STATEMENT
We consider a team of robots operating in a complex
and dynamic maze environment that is populated with
static obstacles of arbitrary geometry and a number
of unpredictable moving obstacles. The configuration
q
i
of each robot is given by the vector q
i
=(x
i
,y
i
)
of the position of its center of mass. We also define
q =(q
1
,q
2
, ..., q
Q
) as the state vector of the robot
team, Q is the number of the robots.
The robots task is to transport materials in a maze,
tracking the shortest path from any starting point to
a defined goal position and avoiding collision with
the environment (fixed obstacles); with their team
members, and with a set of randomly moving, unpre-
dictable dynamic obstacles.
361
Ren J., A. McIsaac K. and Huang X. (2004).
MOTION PLANNING FOR MOBILE ROBOTS IN DYNAMIC ENVIRONMENTS.
In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics, pages 361-364
DOI: 10.5220/0001128503610364
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SciTePress