Abstracting Vehicle Shape and Kinematic Constraints from Obstacle Avoidance Methods |
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Authors: | Javier Minguez Luis Montano José Santos-Victor |
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Affiliation: | (1) Instituto de Investigación en Ingeniería de Aragón, Departamento de Informática e Ingeniería de Sistemas, Universidad de Zaragoza, Spain;(2) Instituto Superior Técnico, Instituto de Sistemas e Robótica, Lisboa, Portugal |
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Abstract: | Most obstacle avoidance techniques do not take into account vehicle shape and kinematic constraints. They assume a punctual
and omnidirectional vehicle and thus they are doomed to rely on approximations when used on real vehicles. Our main contribution
is a framework to consider shape and kinematics together in an exact manner in the obstacle avoidance process, by abstracting
these constraints from the avoidance method usage. Our approach can be applied to many non-holonomic vehicles with arbitrary
shape.
For these vehicles, the configuration space is three-dimensional, while the control space is two-dimensional. The main idea
is to construct (centred on the robot at any time) the two-dimensional manifold of the configuration space that is defined
by elementary circular paths. This manifold contains all the configurations that can be attained at each step of the obstacle
avoidance and is thus general for all methods. Another important contribution of the paper is the exact calculus of the obstacle
representation in this manifold for any robot shape (i.e. the configuration regions in collision). Finally, we propose a change
of coordinates of this manifold so that the elementary paths become straight lines. Therefore, the three-dimensional obstacle
avoidance problem with kinematic constraints is transformed into the simple obstacle avoidance problem for a point moving
in a two-dimensional space without any kinematic restriction (the usual approximation in obstacle avoidance). Thus, existing
avoidance techniques become applicable.
The relevance of this proposal is to improve the domain of applicability of a wide range of obstacle avoidance methods. We
validated the technique by integrating two avoidance methods in our framework and performing tests in the real robot.
Javier Minguez received the physics science degree in 1996 from the Universidad Complutense de Madrid, Madrid, Spain, and the Ph.D. degree
in computer science and systems engineering in 2002 from the University of Zaragoza, Zaragoza, Spain. During his student period,
in 1999 he was a research visitor in the Robotics and Artificial Intelligence Group, LAASCNRS, Toulouse, France. In 2000,
he visited the Robot and ComputerVision Laboratory (ISR-IST), Technical University of Lisbon, Lisbon, Portugal. In 2001, he
was with the Robotics Laboratory, Stanford University, Stanford, USA. He is currently a fulltime Researcher in the Robot,
Vision, and Real Time Group, in the University of Zaragoza. His research interests are obstacle avoidance, motion estimation
and sensor-based motion systems for mobile robots.
Luis Montano was born on September 6, 1958 in Huesca, Spain. He received the industrial engineering degree in 1981 and the PhD degree
in 1987 from the University of Zaragoza, Spain. He is an Associate Professor of Systems Engineering and Automatic Control
at the University of Zaragoza (Spain). He has been Head of the Computer Science and Systems Engineering Department of the
University of Zaragoza.
Currently he is the coordinator of the Production Technologies Research in the Aragon Institute of Engineering Research and
of the Robotics, Perception and Real Time group of the University of Zaragoza. He is principal researcher in robotic projects
and his major research interests are mobile robot navigation and cooperative robots.
José Santos-Victor received the PhD degree in Electrical and Computer Engineering in 1995 from Instituto Superior Técnico (IST - Lisbon, Portugal),
in the area of Computer Vision and Robotics. He is an Associate Professor at the Department of Electrical and Computer Engineering
of IST and a researcher of the Institute of Systems and Robotics (ISR), at the Computer and Robot Vision Lab - VisLab. (http://vislab.isr.ist.utl.pt)
He is the scientific responsible for the participation of IST in various European and National research projects in the areas
of Computer Vision and Robotics. His research interests are in the areas of Computer and Robot Vision, particularly in the
relationship between visual perception and the control of action, biologically inspired vision and robotics, cognitive vision
and visual controlled (land, air and underwater) mobile robots.
Prof. Santos-Victor is an IEEE member and an Associated Editor of the IEEE Transactions on Robotics. |
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Keywords: | obstacle avoidance collision avoidance sensor-based navigation mobile robots |
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