• Corpus ID: 16104326

Probabilistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces

@inproceedings{Faverjon1996ProbabilisticRF,
  title={Probabilistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces},
  author={Bernard Faverjon and Pierre Tournassoud},
  year={1996}
}
Real-time robot motion planning using rasterizing computer graphics hardware. In Proc. OY82] C. O'D unlaing and C.K. Yap. A retraction method for planning the motion of a disc. A local approach for path planning of manipulators with a high number of degrees of freedom. a path generation algorithm into oo-line programming of airbus panels. Motion planning for many degrees of freedom-random reeections at c-space obstacles. REFERENCES 31 iterative collision checker. We observed no dramatic… 

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References

SHOWING 1-5 OF 5 REFERENCES
Robot Motion Planning: A Distributed Representation Approach
We propose a new approach to robot path planning that consists of building and searching a graph connecting the local minima of a potential function defined over the robot's configuration space. A
The complexity of robot motion planning
TLDR
John Canny resolves long-standing problems concerning the complexity of motion planning and, for the central problem of finding a collision free path for a jointed robot in the presence of obstacles, obtains exponential speedups over existing algorithms by applying high-powered new mathematical techniques.
Numerical potential field techniques for robot path planning
The authors investigate a path planning approach that consists of concurrently building and searching a graph connecting the local minima of a numerical potential field defined over the robot's
Using Genetic Algorithms for Robot Motion Planning
TLDR
It is shown that the path planning problem can be expressed as an optimization problem and thus solved with a genetic algorithm and made possible by using the selected genetic algorithm on a massively parallel machine.
SANDROS: a motion planner with performance proportional to task difficulty
  • Pang C. Chen, Y. Hwang
  • Computer Science
    Proceedings 1992 IEEE International Conference on Robotics and Automation
  • 1992
TLDR
This algorithm uses SANDROS, a search strategy that combines hierarchical, nonuniform multiresolution, and best-first search to find a near-optimal solution in the configuration space.