Complete coverage path planning and guidance for cleaning robots

Carvalho, R.N. De; Vidal, H.A.; Vieira, Peter; Ribeiro, Marco

doi:10.1109/isie.1997.649051

Cited by 108 publications

(43 citation statements)

References 2 publications

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“…Using a template based method, the complete trajectory is planned as a sequence of pre-defined trajectories or templates. The template based method introduced by Caravalho et al [5] is able to deal with newly appearing obstacles. Slack's planner [6], which combines APF and Template Based approaches, responds to changes in the environment.…”

Section: Related Workmentioning

confidence: 99%

Optimal area covering using genetic algorithms

Jiménez

Shirinzadeh

Nicholson

et al. 2007

2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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Abstract-Path planning problems involve computing or finding a collision free path between two positions. A special kind of path planning is complete coverage path planning, where a robot sweeps all area of free space in an environment. There are different methods to cover the complete area; however, they are not designed to optimize the process. This paper proposes a novel method of complete coverage path planning based on genetic algorithms. In order to check the viability of this approach the optimal path is tested in a virtual environment. The simulation results confirm the feasibility of this method.

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Section: Related Workmentioning

confidence: 99%

Optimal area covering using genetic algorithms

Jiménez

Shirinzadeh

Nicholson

et al. 2007

2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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“…Path planning is in general a problem concerned with finding paths connecting different locations in an environment, such as a network, a graph, or a geometric space [7]. The desired paths often need to meet specific criteria such as various distance metrics [26,1], cost functions [7], obstacles [22,39] or coverage of an area [9,12]. A well-known problem of path planning is computing shortest paths in graphs (i.e., finding a path in a graph connecting two vertices with the minimum total length) [15,7].…”

Section: Path Planningmentioning

confidence: 99%

MODELING DENDRITIC SHAPES - Using Path Planning

2007

Proceedings of the Second International Conference on Computer Graphics Theory and Applications

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Dendritic shapes are commonplace in the natural world such as trees, lichens, coral and lightning. Models of dendritic shapes are widely needed in many areas. Because of their branching fractal and erratic structures modeling dendritic shapes is a tricky task. Existing methods for modeling dendritic shapes are slow and complicated.In this thesis we present a procedural algorithm of using path planning to model dendritic shapes. We generate a dendrite by finding the least-cost paths from multiple endpoints to a common generator and use the dendrite to build the geometric model. With the control handles of endpoint placement, fractal shape, edge weights distribution and path width, we create different shapes of dendrites that simulate different kinds of dendritic shapes very well. Compared with some existing methods, our algorithm is fast and simple.ii ACKNOWLEDGEMENTS The author would like to express the most sincere thanks to Professor David Mould. He helped me to take the first step and guided me with much kindness and patience. Without him, there is not this thesis.

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“…A specific cleaning trajectory is essential for the cleaning movement to cover all the unoccupied areas in the environment. A lot of research has been devoted to the path planning problem, such as the grid-based method (Zelinsky, A., et al, 1993), the template-based method (Neumann de Carvalho, R. et al, 1997) and the neural network approach (Yang, S.H. et al, 2004).…”

Section: Characteristics Of Path Planning For Wall Cleaning Robotsmentioning

confidence: 99%