The Ariadne's clew algorithm

Authors:
Emmanuel Mazer;Juan Manuel Ahuactzin;Pierre Bessiére
Affiliations:
Laboratoire GRAVIR, Montbonnot, France;Depto. de Ing. en Sistemas Computationales, Universidad de las Americas,;Laboratoire LEIBNIZ, Grenoble, France
Venue:
Journal of Artificial Intelligence Research
Year:
1998

Citing 7
Cited 11

Parallel implementation of genetic algorithms in a classifier system

Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Parallel genetic algorithms for a hypercube

Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
The complexity of robot motion planning

The complexity of robot motion planning
Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Gross motion planning—a survey

ACM Computing Surveys (CSUR)
Using genetic algorithms for robot motion planning

ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Analogous Crossover

Proceedings of the 3rd International Conference on Genetic Algorithms

Dynamically-Stable Motion Planning for Humanoid Robots

Autonomous Robots
Path Planning Using a Single-Query Bi-directional Lazy Collision Checking Planner

MICAI '02 Proceedings of the Second Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
The dynamic wave expansion neural network model for robot motion planning in time-varying environments

Neural Networks
Path planning with general end-effector constraints

Robotics and Autonomous Systems
Progressive Optimisation of Organised Colonies of Ants for Robot Navigation: An Inspiration from Nature

ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
An Evolutionary Path Planner for Multiple Robot Arms

EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Chaotic bee swarm optimization algorithm for path planning of mobile robots

EC'09 Proceedings of the 10th WSEAS international conference on evolutionary computing
A Survey of Motion Planning Algorithms from the Perspective of Autonomous UAV Guidance

Journal of Intelligent and Robotic Systems
Path planning for manipulator robots in cluttered environments

ACMOS'05 Proceedings of the 7th WSEAS international conference on Automatic control, modeling and simulation
Algorithmic motion planning: the randomized approach

General Theory of Information Transfer and Combinatorics
Understanding motion planning better: A comparative review of “Principles of Robot Motion: Theory, Algorithms, and Implementations”, by H. Choset et-al.

Computer Science Review

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a new approach to path planning, called the "Ariadne's clew algorithm". It is designed to find paths in high-dimensional continuous spaces and applies to robots with many degrees of freedom in static, as well as dynamic environments -- ones where obstacles may move. The Ariadne's clew algorithm comprises two sub-algorithms, called SEARCH and EXPLORE, applied in an interleaved manner. EXPLORE builds a representation of the accessible space while SEARCH looks for the target. Both are posed as optimization problems. We describe a real implementation of the algorithm to plan paths for a six degrees of freedom arm in a dynamic environment where another six degrees of freedom arm is used as a moving obstacle. Experimental results show that a path is found in about one second without any pre-processing.