Fast design of the QP-based optimal trajectory for a motion simulator View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2007-12

AUTHORS

Young Man Cho, Hwa Soo Kim, Ik Kyu Kim, Jong Jin Woo, Jongwon Kim

ABSTRACT

The main difficulty in realizing a motion simulator comes from the constraints on its workspace. The so-called washout filter prevents a simulator from being driven to go off its pre-determined boundaries and generate excessive torques. By noting that the existing washout filters are conservative and more aggressive motions may be accommodated, this paper presents a novel approach that fully exploits the simulator workspace and thereby reproduces the real-world sensations with high fidelity. The washout filter converts the real-world input trajectory as a realizable one that satisfies the spatial and dynamic constraints while minimizing the sensation error and fidelity between the motions experienced in the real world and on the motion simulator. The control objective is to reduce the computational burdens by using the QP algorithm. The proposed approach formulates the task of designing a washout filter as a quadratic programming (QP). The direct approach to the solution of the QP often results in a computational burden that amounts toO(N3) flops andO(N2) storage space (N=104 ∼ 105, typically). By judiciously exploiting the Toeplitz structures of the underlying matrices, an orders-of-magnitude faster algorithm is obtained to reduce the computational burdens toO(Nlog2N) flops andO(N) storage space. The extensive simulation studies on the Eclipse-II motion simulator at Seoul National University assure that the QP-based fast algorithm outperforms the existing ones in reproducing the real-world sensations. More... »

PAGES

1973

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf03177455

DOI

http://dx.doi.org/10.1007/bf03177455

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1036391991


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Seoul National University", 
          "id": "https://www.grid.ac/institutes/grid.31501.36", 
          "name": [
            "School of Mechanical and Aerospace Engineering, Seoul National Univ, 151-744, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cho", 
        "givenName": "Young Man", 
        "id": "sg:person.012176153337.61", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012176153337.61"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Seoul National University", 
          "id": "https://www.grid.ac/institutes/grid.31501.36", 
          "name": [
            "School of Mechanical and Aerospace Engineering, Seoul National Univ, 151-744, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kim", 
        "givenName": "Hwa Soo", 
        "id": "sg:person.016513155261.16", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016513155261.16"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Seoul National University", 
          "id": "https://www.grid.ac/institutes/grid.31501.36", 
          "name": [
            "School of Mechanical and Aerospace Engineering, Seoul National Univ, 151-744, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kim", 
        "givenName": "Ik Kyu", 
        "id": "sg:person.07476057131.88", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07476057131.88"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Seoul National University", 
          "id": "https://www.grid.ac/institutes/grid.31501.36", 
          "name": [
            "School of Mechanical and Aerospace Engineering, Seoul National Univ, 151-744, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Woo", 
        "givenName": "Jong Jin", 
        "id": "sg:person.010273437531.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010273437531.22"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Seoul National University", 
          "id": "https://www.grid.ac/institutes/grid.31501.36", 
          "name": [
            "School of Mechanical and Aerospace Engineering, Seoul National Univ, 151-744, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kim", 
        "givenName": "Jongwon", 
        "id": "sg:person.013611426734.26", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013611426734.26"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/bf02916145", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000094054", 
          "https://doi.org/10.1007/bf02916145"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02916145", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000094054", 
          "https://doi.org/10.1007/bf02916145"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2514/3.20846", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005660191"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02984393", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018219278", 
          "https://doi.org/10.1007/bf02984393"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2514/6.2000-4291", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024424282"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tra.2002.1019472", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061784137"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/robot.1997.606801", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093184714"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2007-12", 
    "datePublishedReg": "2007-12-01", 
    "description": "The main difficulty in realizing a motion simulator comes from the constraints on its workspace. The so-called washout filter prevents a simulator from being driven to go off its pre-determined boundaries and generate excessive torques. By noting that the existing washout filters are conservative and more aggressive motions may be accommodated, this paper presents a novel approach that fully exploits the simulator workspace and thereby reproduces the real-world sensations with high fidelity. The washout filter converts the real-world input trajectory as a realizable one that satisfies the spatial and dynamic constraints while minimizing the sensation error and fidelity between the motions experienced in the real world and on the motion simulator. The control objective is to reduce the computational burdens by using the QP algorithm. The proposed approach formulates the task of designing a washout filter as a quadratic programming (QP). The direct approach to the solution of the QP often results in a computational burden that amounts toO(N3) flops andO(N2) storage space (N=104 \u223c 105, typically). By judiciously exploiting the Toeplitz structures of the underlying matrices, an orders-of-magnitude faster algorithm is obtained to reduce the computational burdens toO(Nlog2N) flops andO(N) storage space. The extensive simulation studies on the Eclipse-II motion simulator at Seoul National University assure that the QP-based fast algorithm outperforms the existing ones in reproducing the real-world sensations.", 
    "genre": "non_research_article", 
    "id": "sg:pub.10.1007/bf03177455", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1295111", 
        "issn": [
          "1011-8861", 
          "1226-4865"
        ], 
        "name": "Journal of Mechanical Science and Technology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "12", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "21"
      }
    ], 
    "name": "Fast design of the QP-based optimal trajectory for a motion simulator", 
    "pagination": "1973", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "ad5b9c994d0f5f1db2940450245a1fa928181e107046aef57d303cfc59639d7c"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/bf03177455"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1036391991"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/bf03177455", 
      "https://app.dimensions.ai/details/publication/pub.1036391991"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T14:33", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000373_0000000373/records_13104_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2FBF03177455"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/bf03177455'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/bf03177455'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/bf03177455'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/bf03177455'


 

This table displays all metadata directly associated to this object as RDF triples.

109 TRIPLES      21 PREDICATES      33 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/bf03177455 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author N4e772b346aa84fce8c371b291e6ae83a
4 schema:citation sg:pub.10.1007/bf02916145
5 sg:pub.10.1007/bf02984393
6 https://doi.org/10.1109/robot.1997.606801
7 https://doi.org/10.1109/tra.2002.1019472
8 https://doi.org/10.2514/3.20846
9 https://doi.org/10.2514/6.2000-4291
10 schema:datePublished 2007-12
11 schema:datePublishedReg 2007-12-01
12 schema:description The main difficulty in realizing a motion simulator comes from the constraints on its workspace. The so-called washout filter prevents a simulator from being driven to go off its pre-determined boundaries and generate excessive torques. By noting that the existing washout filters are conservative and more aggressive motions may be accommodated, this paper presents a novel approach that fully exploits the simulator workspace and thereby reproduces the real-world sensations with high fidelity. The washout filter converts the real-world input trajectory as a realizable one that satisfies the spatial and dynamic constraints while minimizing the sensation error and fidelity between the motions experienced in the real world and on the motion simulator. The control objective is to reduce the computational burdens by using the QP algorithm. The proposed approach formulates the task of designing a washout filter as a quadratic programming (QP). The direct approach to the solution of the QP often results in a computational burden that amounts toO(N3) flops andO(N2) storage space (N=104 ∼ 105, typically). By judiciously exploiting the Toeplitz structures of the underlying matrices, an orders-of-magnitude faster algorithm is obtained to reduce the computational burdens toO(Nlog2N) flops andO(N) storage space. The extensive simulation studies on the Eclipse-II motion simulator at Seoul National University assure that the QP-based fast algorithm outperforms the existing ones in reproducing the real-world sensations.
13 schema:genre non_research_article
14 schema:inLanguage en
15 schema:isAccessibleForFree false
16 schema:isPartOf N0a59719c7e5c4971a9e92e0ab011e77b
17 Ne299f7baf4e94b369a102678ed090da7
18 sg:journal.1295111
19 schema:name Fast design of the QP-based optimal trajectory for a motion simulator
20 schema:pagination 1973
21 schema:productId N355f40c4feea40d9a932f3e047dac950
22 N90f833f79e5e419cad8705fda8eda995
23 Nf6c80995cd89406493b65540abb54029
24 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036391991
25 https://doi.org/10.1007/bf03177455
26 schema:sdDatePublished 2019-04-11T14:33
27 schema:sdLicense https://scigraph.springernature.com/explorer/license/
28 schema:sdPublisher Nd1b49d4d0d314a9ba33bb94933965c4a
29 schema:url http://link.springer.com/10.1007%2FBF03177455
30 sgo:license sg:explorer/license/
31 sgo:sdDataset articles
32 rdf:type schema:ScholarlyArticle
33 N0a59719c7e5c4971a9e92e0ab011e77b schema:volumeNumber 21
34 rdf:type schema:PublicationVolume
35 N2acf197453554797935a43ff14391dd4 rdf:first sg:person.013611426734.26
36 rdf:rest rdf:nil
37 N355f40c4feea40d9a932f3e047dac950 schema:name doi
38 schema:value 10.1007/bf03177455
39 rdf:type schema:PropertyValue
40 N3a66285022e54bf9a5ebb261c39bb6c1 rdf:first sg:person.010273437531.22
41 rdf:rest N2acf197453554797935a43ff14391dd4
42 N4e772b346aa84fce8c371b291e6ae83a rdf:first sg:person.012176153337.61
43 rdf:rest Nb6ce8b4e7e834e989468df9ae6fd3815
44 N90f833f79e5e419cad8705fda8eda995 schema:name readcube_id
45 schema:value ad5b9c994d0f5f1db2940450245a1fa928181e107046aef57d303cfc59639d7c
46 rdf:type schema:PropertyValue
47 Nb6ce8b4e7e834e989468df9ae6fd3815 rdf:first sg:person.016513155261.16
48 rdf:rest Nfc7542b0dc664b7f98c2aa7eee1c8e7b
49 Nd1b49d4d0d314a9ba33bb94933965c4a schema:name Springer Nature - SN SciGraph project
50 rdf:type schema:Organization
51 Ne299f7baf4e94b369a102678ed090da7 schema:issueNumber 12
52 rdf:type schema:PublicationIssue
53 Nf6c80995cd89406493b65540abb54029 schema:name dimensions_id
54 schema:value pub.1036391991
55 rdf:type schema:PropertyValue
56 Nfc7542b0dc664b7f98c2aa7eee1c8e7b rdf:first sg:person.07476057131.88
57 rdf:rest N3a66285022e54bf9a5ebb261c39bb6c1
58 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
59 schema:name Information and Computing Sciences
60 rdf:type schema:DefinedTerm
61 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
62 schema:name Artificial Intelligence and Image Processing
63 rdf:type schema:DefinedTerm
64 sg:journal.1295111 schema:issn 1011-8861
65 1226-4865
66 schema:name Journal of Mechanical Science and Technology
67 rdf:type schema:Periodical
68 sg:person.010273437531.22 schema:affiliation https://www.grid.ac/institutes/grid.31501.36
69 schema:familyName Woo
70 schema:givenName Jong Jin
71 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010273437531.22
72 rdf:type schema:Person
73 sg:person.012176153337.61 schema:affiliation https://www.grid.ac/institutes/grid.31501.36
74 schema:familyName Cho
75 schema:givenName Young Man
76 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012176153337.61
77 rdf:type schema:Person
78 sg:person.013611426734.26 schema:affiliation https://www.grid.ac/institutes/grid.31501.36
79 schema:familyName Kim
80 schema:givenName Jongwon
81 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013611426734.26
82 rdf:type schema:Person
83 sg:person.016513155261.16 schema:affiliation https://www.grid.ac/institutes/grid.31501.36
84 schema:familyName Kim
85 schema:givenName Hwa Soo
86 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016513155261.16
87 rdf:type schema:Person
88 sg:person.07476057131.88 schema:affiliation https://www.grid.ac/institutes/grid.31501.36
89 schema:familyName Kim
90 schema:givenName Ik Kyu
91 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07476057131.88
92 rdf:type schema:Person
93 sg:pub.10.1007/bf02916145 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000094054
94 https://doi.org/10.1007/bf02916145
95 rdf:type schema:CreativeWork
96 sg:pub.10.1007/bf02984393 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018219278
97 https://doi.org/10.1007/bf02984393
98 rdf:type schema:CreativeWork
99 https://doi.org/10.1109/robot.1997.606801 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093184714
100 rdf:type schema:CreativeWork
101 https://doi.org/10.1109/tra.2002.1019472 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061784137
102 rdf:type schema:CreativeWork
103 https://doi.org/10.2514/3.20846 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005660191
104 rdf:type schema:CreativeWork
105 https://doi.org/10.2514/6.2000-4291 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024424282
106 rdf:type schema:CreativeWork
107 https://www.grid.ac/institutes/grid.31501.36 schema:alternateName Seoul National University
108 schema:name School of Mechanical and Aerospace Engineering, Seoul National Univ, 151-744, Seoul, Korea
109 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...