Spline-based RRT path planner for non-holonomic robots

Kwangjin Yang; Sangwoo Moon; Seunghoon Yoo; Jaehyeon Kang; Nakju Lett Doh; Hong Bong Kim; Sanghyun Joo

doi:10.1007/s10846-013-9963-y

Spline-based RRT path planner for non-holonomic robots

Kwangjin Yang, Sangwoo Moon, Seunghoon Yoo, Jaehyeon Kang, Nakju Lett Doh, Hong Bong Kim, Sanghyun Joo

Research output: Contribution to journal › Article › peer-review

93 Citations (Scopus)

Abstract

Planning in a cluttered environment under differential constraints is a difficult problem because the planner must satisfy the external constraints that arise from obstacles in the environment and the internal constraints due to the kinematic/dynamic limitations of the robot. This paper proposes a novel Spline-based Rapidlyexploring Random Tree (SRRT) algorithm which treats both the external and internal constraints simultaneously and efficiently. The computationally expensive numerical integration of the system dynamics is replaced by an efficient spline curve parameterization. In addition, the SRRT guarantees continuity of curvature along the path satisfying any upper-bounded curvature constraints. This paper presents the underlying theory to the SRRT algorithm and presents simulation and experiment results of a mobile robot efficiently navigating through cluttered environments.

Original language	English
Pages (from-to)	763-782
Number of pages	20
Journal	Journal of Intelligent and Robotic Systems: Theory and Applications
Volume	73
Issue number	1-4
DOIs	https://doi.org/10.1007/s10846-013-9963-y
Publication status	Published - 2014 Jan

Bibliographical note

Funding Information:
This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2012R1A1A4A01005563).

Keywords

Differential constraints
Mobile robot
Rapidly-exploring random tree
Spline curve parameterization

ASJC Scopus subject areas

Software
Mechanical Engineering
Artificial Intelligence
Electrical and Electronic Engineering
Control and Systems Engineering
Industrial and Manufacturing Engineering

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10.1007/s10846-013-9963-y

Cite this

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abstract = "Planning in a cluttered environment under differential constraints is a difficult problem because the planner must satisfy the external constraints that arise from obstacles in the environment and the internal constraints due to the kinematic/dynamic limitations of the robot. This paper proposes a novel Spline-based Rapidlyexploring Random Tree (SRRT) algorithm which treats both the external and internal constraints simultaneously and efficiently. The computationally expensive numerical integration of the system dynamics is replaced by an efficient spline curve parameterization. In addition, the SRRT guarantees continuity of curvature along the path satisfying any upper-bounded curvature constraints. This paper presents the underlying theory to the SRRT algorithm and presents simulation and experiment results of a mobile robot efficiently navigating through cluttered environments.",

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AU - Moon, Sangwoo

AU - Yoo, Seunghoon

AU - Kang, Jaehyeon

AU - Doh, Nakju Lett

AU - Kim, Hong Bong

AU - Joo, Sanghyun

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N2 - Planning in a cluttered environment under differential constraints is a difficult problem because the planner must satisfy the external constraints that arise from obstacles in the environment and the internal constraints due to the kinematic/dynamic limitations of the robot. This paper proposes a novel Spline-based Rapidlyexploring Random Tree (SRRT) algorithm which treats both the external and internal constraints simultaneously and efficiently. The computationally expensive numerical integration of the system dynamics is replaced by an efficient spline curve parameterization. In addition, the SRRT guarantees continuity of curvature along the path satisfying any upper-bounded curvature constraints. This paper presents the underlying theory to the SRRT algorithm and presents simulation and experiment results of a mobile robot efficiently navigating through cluttered environments.

AB - Planning in a cluttered environment under differential constraints is a difficult problem because the planner must satisfy the external constraints that arise from obstacles in the environment and the internal constraints due to the kinematic/dynamic limitations of the robot. This paper proposes a novel Spline-based Rapidlyexploring Random Tree (SRRT) algorithm which treats both the external and internal constraints simultaneously and efficiently. The computationally expensive numerical integration of the system dynamics is replaced by an efficient spline curve parameterization. In addition, the SRRT guarantees continuity of curvature along the path satisfying any upper-bounded curvature constraints. This paper presents the underlying theory to the SRRT algorithm and presents simulation and experiment results of a mobile robot efficiently navigating through cluttered environments.

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Spline-based RRT path planner for non-holonomic robots

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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