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Lift path planning for a nonholonomic crawler crane.

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Title: Lift path planning for a nonholonomic crawler crane.
Authors: Lin, Yuanshan1,2 Linyuanshan2008@126.com, Wu, Di3 wudi@dlut.edu.cn, Wang, Xin4 Wangxbd21@163.com, Wang, Xiukun3 Jsjwxk@dlut.edu.cn, Gao, Shunde4 gaoshunde@163.com
Source: Automation in Construction. Aug2014, Vol. 44, p12-24. 13p.
Subjects: Elevators, Nonholonomic dynamical systems, Cranes (Machinery), Kinematics, Collisions (Physics), Automation
Abstract: Abstract: This paper presents an efficient lift path planning approach for a crawler crane in which the mobility of the crawler crane and its nonholonomic kinematics are considered. To obtain the optimal path rapidly, we improved the bidirectional Rapidly exploring Random Trees (RRTs) using a sampling strategy and an expansion strategy. The sampling strategy of choosing a sample from a sampling pool and unexplored space was applied to guide trees towards the collision-free and high-quality region. Furthermore, the expansion strategy of extending one tree every other k steps was introduced to increase the chance of connecting to the other tree while ensuring that the trees have a small amount of nodes. The proposed approach was tested on three lift problems. The results indicate that the approach can generate high-quality paths in complex situations in a short time, and the paths satisfy the collision constraint, lifting capacity constraint and nonholonomic kinematics constraints of the crawler crane. [Copyright &y& Elsevier]
Copyright of Automation in Construction is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 96447316
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
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  Data: Lift path planning for a nonholonomic crawler crane.
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  Data: <searchLink fieldCode="AR" term="%22Lin%2C+Yuanshan%22">Lin, Yuanshan</searchLink><relatesTo>1,2</relatesTo><i> Linyuanshan2008@126.com</i><br /><searchLink fieldCode="AR" term="%22Wu%2C+Di%22">Wu, Di</searchLink><relatesTo>3</relatesTo><i> wudi@dlut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Xin%22">Wang, Xin</searchLink><relatesTo>4</relatesTo><i> Wangxbd21@163.com</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Xiukun%22">Wang, Xiukun</searchLink><relatesTo>3</relatesTo><i> Jsjwxk@dlut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Gao%2C+Shunde%22">Gao, Shunde</searchLink><relatesTo>4</relatesTo><i> gaoshunde@163.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Automation+in+Construction%22">Automation in Construction</searchLink>. Aug2014, Vol. 44, p12-24. 13p.
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  Data: <searchLink fieldCode="DE" term="%22Elevators%22">Elevators</searchLink><br /><searchLink fieldCode="DE" term="%22Nonholonomic+dynamical+systems%22">Nonholonomic dynamical systems</searchLink><br /><searchLink fieldCode="DE" term="%22Cranes+%28Machinery%29%22">Cranes (Machinery)</searchLink><br /><searchLink fieldCode="DE" term="%22Kinematics%22">Kinematics</searchLink><br /><searchLink fieldCode="DE" term="%22Collisions+%28Physics%29%22">Collisions (Physics)</searchLink><br /><searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Abstract: This paper presents an efficient lift path planning approach for a crawler crane in which the mobility of the crawler crane and its nonholonomic kinematics are considered. To obtain the optimal path rapidly, we improved the bidirectional Rapidly exploring Random Trees (RRTs) using a sampling strategy and an expansion strategy. The sampling strategy of choosing a sample from a sampling pool and unexplored space was applied to guide trees towards the collision-free and high-quality region. Furthermore, the expansion strategy of extending one tree every other k steps was introduced to increase the chance of connecting to the other tree while ensuring that the trees have a small amount of nodes. The proposed approach was tested on three lift problems. The results indicate that the approach can generate high-quality paths in complex situations in a short time, and the paths satisfy the collision constraint, lifting capacity constraint and nonholonomic kinematics constraints of the crawler crane. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Automation in Construction is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.autcon.2014.03.007
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 13
        StartPage: 12
    Subjects:
      – SubjectFull: Elevators
        Type: general
      – SubjectFull: Nonholonomic dynamical systems
        Type: general
      – SubjectFull: Cranes (Machinery)
        Type: general
      – SubjectFull: Kinematics
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      – SubjectFull: Collisions (Physics)
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      – SubjectFull: Automation
        Type: general
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      – TitleFull: Lift path planning for a nonholonomic crawler crane.
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            NameFull: Lin, Yuanshan
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            NameFull: Wu, Di
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            NameFull: Wang, Xin
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            NameFull: Wang, Xiukun
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              M: 08
              Text: Aug2014
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              Y: 2014
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              Value: 44
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