Revisiting bounded-suboptimal safe interval path planning

Konstantin Yakovlev; Anton Andreychuk; Roni Stern

doi:10.1609/icaps.v30i1.6674

Revisiting bounded-suboptimal safe interval path planning

Konstantin Yakovlev, Anton Andreychuk, Roni Stern

Department of Software and Information Systems Engineering

Research output: Contribution to journal › Conference article › peer-review

14 Scopus citations

Abstract

Safe-interval path planning (SIPP) is a powerful algorithm for finding a path in the presence of dynamic obstacles. SIPP returns provably optimal solutions. However, in many practical applications of SIPP such as path planning for robots, one would like to trade-off optimality for shorter planning time. In this paper we explore different ways to build a bounded-suboptimal SIPP and discuss their pros and cons. We compare the different bounded-suboptimal versions of SIPP experimentally. While there is no universal winner, the results provide insights into when each method should be used.

Original language	English
Pages (from-to)	300-304
Number of pages	5
Journal	Proceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume	30
DOIs	https://doi.org/10.1609/icaps.v30i1.6674
State	Published - 29 May 2020
Event	30th International Conference on Automated Planning and Scheduling, ICAPS 2020 - Nancy, France Duration: 26 Oct 2020 → 30 Oct 2020

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Information Systems and Management

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10.1609/icaps.v30i1.6674

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abstract = "Safe-interval path planning (SIPP) is a powerful algorithm for finding a path in the presence of dynamic obstacles. SIPP returns provably optimal solutions. However, in many practical applications of SIPP such as path planning for robots, one would like to trade-off optimality for shorter planning time. In this paper we explore different ways to build a bounded-suboptimal SIPP and discuss their pros and cons. We compare the different bounded-suboptimal versions of SIPP experimentally. While there is no universal winner, the results provide insights into when each method should be used.",

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AU - Andreychuk, Anton

AU - Stern, Roni

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AB - Safe-interval path planning (SIPP) is a powerful algorithm for finding a path in the presence of dynamic obstacles. SIPP returns provably optimal solutions. However, in many practical applications of SIPP such as path planning for robots, one would like to trade-off optimality for shorter planning time. In this paper we explore different ways to build a bounded-suboptimal SIPP and discuss their pros and cons. We compare the different bounded-suboptimal versions of SIPP experimentally. While there is no universal winner, the results provide insights into when each method should be used.

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T2 - 30th International Conference on Automated Planning and Scheduling, ICAPS 2020

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ER -

Revisiting bounded-suboptimal safe interval path planning

Abstract

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