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Real-time collision-free
motion planning of nonholonomic robots using a neural dynamics
based approach
Xu, H.
Yang,
S.X.
Sch. of
Eng., Guelph Univ., Ont.;
This paper appears in: Robotics and
Automation, 2002. Proceedings. ICRA '02. IEEE International
Conference on
05/11/2002 -05/15/2002, 2002
Location: Washington, DC , USA
On page(s): 3087-3092
2002
References
Cited: 11
Number of Pages:
4 vol.lxxiv+4353
INSPEC
Accession Number: 7379503
Abstract:
A novel neural dynamics based approach to
smooth, continuous and collision-free path generation of an
autonomous nonholonomic mobile robot is proposed. The robot
behavior, such as target acquisition and obstacle avoidance,
are completely controlled by two control variables, the
heading direction and the forward velocity of the robot. The
dynamics of these control variables is characterized by a
biologically inspired shunting neural model, whose inputs are
from the target and obstacles that are acquired relying on
measurable sensors information only. The target input produces
an attractive force, while the obstacle inputs form repulsive
forces to the mobile robot. Each force votes for a certain
value of control variables that have unique values at a
certain time. The collision-free path and the velocity control
commands of the robot are generated through the dynamics of
control variables. The kinematic constraints of mobile robot
is respected. A series of simulation results show that the
proposed approach can be successfully applied to both static
and dynamic environments, as well as multi-robot systems with
effective and efficient computation
Index Terms:
mobile
robots neural
nets path
planning real-time
systems time
series
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