### Abstract

Computing the configuration space is an important problem in spatial planning for robotics applications. In this paper, we present parallel algorithms for computing the configuration space by using hypercube multiprocessors. The digitized images of the obstacles and the robot are stored in an N×N image plane. In this paper, we develop optimal hypercube algorithms to compute the configuration space for circle and rectangle shaped robots. We also develop several new basic hypercube operations. The time complexity of all the algorithms is O (logN) and is asymptotically optimal for hypercube computers. The space complexity of each processor is O (1) which is again optimal.

Original language | English |
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Pages | 182-186 |

Number of pages | 5 |

State | Published - 1 Jan 1995 |

Event | Proceedings of the 1995 ACM Symposium on Applied Computing - Nashville, TN, USA Duration: 26 Feb 1995 → 28 Feb 1995 |

### Other

Other | Proceedings of the 1995 ACM Symposium on Applied Computing |
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City | Nashville, TN, USA |

Period | 26/02/95 → 28/02/95 |

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### Cite this

*Optimal hypercube algorithms for robot configuration space computation*. 182-186. Paper presented at Proceedings of the 1995 ACM Symposium on Applied Computing, Nashville, TN, USA, .

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**Optimal hypercube algorithms for robot configuration space computation.** / Jenq, John; Li, Wing Ning.

Research output: Contribution to conference › Paper

TY - CONF

T1 - Optimal hypercube algorithms for robot configuration space computation

AU - Jenq, John

AU - Li, Wing Ning

PY - 1995/1/1

Y1 - 1995/1/1

N2 - Computing the configuration space is an important problem in spatial planning for robotics applications. In this paper, we present parallel algorithms for computing the configuration space by using hypercube multiprocessors. The digitized images of the obstacles and the robot are stored in an N×N image plane. In this paper, we develop optimal hypercube algorithms to compute the configuration space for circle and rectangle shaped robots. We also develop several new basic hypercube operations. The time complexity of all the algorithms is O (logN) and is asymptotically optimal for hypercube computers. The space complexity of each processor is O (1) which is again optimal.

AB - Computing the configuration space is an important problem in spatial planning for robotics applications. In this paper, we present parallel algorithms for computing the configuration space by using hypercube multiprocessors. The digitized images of the obstacles and the robot are stored in an N×N image plane. In this paper, we develop optimal hypercube algorithms to compute the configuration space for circle and rectangle shaped robots. We also develop several new basic hypercube operations. The time complexity of all the algorithms is O (logN) and is asymptotically optimal for hypercube computers. The space complexity of each processor is O (1) which is again optimal.

UR - http://www.scopus.com/inward/record.url?scp=0029204015&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0029204015

SP - 182

EP - 186

ER -