Anytime path planning in graduated state space

Haojie Zhang; Guangming Xiong; Bo Su; Jianwei Gong; Yan Jiang; Huiyan Chen; Wei Lan

doi:10.1109/IVS.2013.6629495

Anytime path planning in graduated state space

Haojie Zhang, Guangming Xiong^*, Bo Su, Jianwei Gong, Yan Jiang, Huiyan Chen, Wei Lan

^*Corresponding author for this work

School of Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

Complex robotic systems often have to operate in large environments. At the same time, their dynamic is complex enough that path planning algorithms need to reason about the kinodynamic constraints of these systems. On the other hand, such roboticsystems are typically expected to operate with speed that is commensurate with that of humans. This poses stringent limitation on available planning time. These will result in a contradiction between planning efficiency and the dimensions of the state space determined by the kinodynamic constraints. In this paper we present an anytime path planning algorithm to solving this problem. First, a graduated state space which consists of state lattices and grids is constructed for planning. Then, ARA algorithm is utilized to search the graduated state space to find a path that satisfies the kinodynamic constraints and available runtime of planning.

Original language	English
Title of host publication	2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013
Pages	358-362
Number of pages	5
DOIs	https://doi.org/10.1109/IVS.2013.6629495
Publication status	Published - 2013
Event	2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013 - Gold Coast, QLD, Australia Duration: 23 Jun 2013 → 26 Jun 2013

Publication series

Name	IEEE Intelligent Vehicles Symposium, Proceedings

Conference

Conference	2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013
Country/Territory	Australia
City	Gold Coast, QLD
Period	23/06/13 → 26/06/13

Access to Document

10.1109/IVS.2013.6629495

Cite this

@inproceedings{701c5bb9809945a5b84994b77c6ffd03,

title = "Anytime path planning in graduated state space",

abstract = "Complex robotic systems often have to operate in large environments. At the same time, their dynamic is complex enough that path planning algorithms need to reason about the kinodynamic constraints of these systems. On the other hand, such roboticsystems are typically expected to operate with speed that is commensurate with that of humans. This poses stringent limitation on available planning time. These will result in a contradiction between planning efficiency and the dimensions of the state space determined by the kinodynamic constraints. In this paper we present an anytime path planning algorithm to solving this problem. First, a graduated state space which consists of state lattices and grids is constructed for planning. Then, ARA algorithm is utilized to search the graduated state space to find a path that satisfies the kinodynamic constraints and available runtime of planning.",

author = "Haojie Zhang and Guangming Xiong and Bo Su and Jianwei Gong and Yan Jiang and Huiyan Chen and Wei Lan",

year = "2013",

doi = "10.1109/IVS.2013.6629495",

language = "English",

isbn = "9781467327558",

series = "IEEE Intelligent Vehicles Symposium, Proceedings",

pages = "358--362",

booktitle = "2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013",

note = "2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013 ; Conference date: 23-06-2013 Through 26-06-2013",

}

Zhang, H, Xiong, G, Su, B, Gong, J, Jiang, Y, Chen, H & Lan, W 2013, Anytime path planning in graduated state space. in 2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013., 6629495, IEEE Intelligent Vehicles Symposium, Proceedings, pp. 358-362, 2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013, Gold Coast, QLD, Australia, 23/06/13. https://doi.org/10.1109/IVS.2013.6629495

TY - GEN

T1 - Anytime path planning in graduated state space

AU - Zhang, Haojie

AU - Xiong, Guangming

AU - Su, Bo

AU - Gong, Jianwei

AU - Jiang, Yan

AU - Chen, Huiyan

AU - Lan, Wei

PY - 2013

Y1 - 2013

N2 - Complex robotic systems often have to operate in large environments. At the same time, their dynamic is complex enough that path planning algorithms need to reason about the kinodynamic constraints of these systems. On the other hand, such roboticsystems are typically expected to operate with speed that is commensurate with that of humans. This poses stringent limitation on available planning time. These will result in a contradiction between planning efficiency and the dimensions of the state space determined by the kinodynamic constraints. In this paper we present an anytime path planning algorithm to solving this problem. First, a graduated state space which consists of state lattices and grids is constructed for planning. Then, ARA algorithm is utilized to search the graduated state space to find a path that satisfies the kinodynamic constraints and available runtime of planning.

AB - Complex robotic systems often have to operate in large environments. At the same time, their dynamic is complex enough that path planning algorithms need to reason about the kinodynamic constraints of these systems. On the other hand, such roboticsystems are typically expected to operate with speed that is commensurate with that of humans. This poses stringent limitation on available planning time. These will result in a contradiction between planning efficiency and the dimensions of the state space determined by the kinodynamic constraints. In this paper we present an anytime path planning algorithm to solving this problem. First, a graduated state space which consists of state lattices and grids is constructed for planning. Then, ARA algorithm is utilized to search the graduated state space to find a path that satisfies the kinodynamic constraints and available runtime of planning.

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U2 - 10.1109/IVS.2013.6629495

DO - 10.1109/IVS.2013.6629495

M3 - Conference contribution

AN - SCOPUS:84892416996

SN - 9781467327558

T3 - IEEE Intelligent Vehicles Symposium, Proceedings

SP - 358

EP - 362

BT - 2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013

T2 - 2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013

Y2 - 23 June 2013 through 26 June 2013

ER -

Anytime path planning in graduated state space

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