Generating Reactive Virtual Guidance Fixtures for Assisted Telemanipulation Tasks
In this work, we propose the generation of a tube-shaped virtual fixture that guides the operator towards a target position. This position is obtained through a HumanMachine Interface (HMI) and it is used to adapt the endpoint of the virtual fixture by means of a reactive constraint-based approach....
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| creator | Iregui Rincon, Santiago Vergara, Cristian De Schutter, Joris Aertbeliën, Erwin |
| description | In this work, we propose the generation of a
tube-shaped virtual fixture that guides the operator towards
a target position. This position is obtained through a HumanMachine Interface (HMI) and it is used to adapt the endpoint
of the virtual fixture by means of a reactive constraint-based
approach. In parallel, a target object is inferred in realtime through a Bayesian intent estimation algorithm that uses
information coming from a vision system and the HMI. A
shared control strategy is then used to attract the endpoint of
the virtual fixture towards the inferred target object. The path
of this reactive virtual fixture also adapts to avoid collisions
with dynamic obstacles. With our approach, we expect to
reduce the effort and fatigue of the operators when performing
telemanipulation tasks. |
| format | Other |
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tube-shaped virtual fixture that guides the operator towards
a target position. This position is obtained through a HumanMachine Interface (HMI) and it is used to adapt the endpoint
of the virtual fixture by means of a reactive constraint-based
approach. In parallel, a target object is inferred in realtime through a Bayesian intent estimation algorithm that uses
information coming from a vision system and the HMI. A
shared control strategy is then used to attract the endpoint of
the virtual fixture towards the inferred target object. The path
of this reactive virtual fixture also adapts to avoid collisions
with dynamic obstacles. With our approach, we expect to
reduce the effort and fatigue of the operators when performing
telemanipulation tasks.</description><language>eng</language><creationdate>2020</creationdate><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,776,27837</link.rule.ids><linktorsrc>$$Uhttps://lirias.kuleuven.be/handle/123456789/656391$$EView_record_in_KU_Leuven_Association$$FView_record_in_$$GKU_Leuven_Association</linktorsrc></links><search><creatorcontrib>Iregui Rincon, Santiago</creatorcontrib><creatorcontrib>Vergara, Cristian</creatorcontrib><creatorcontrib>De Schutter, Joris</creatorcontrib><creatorcontrib>Aertbeliën, Erwin</creatorcontrib><title>Generating Reactive Virtual Guidance Fixtures for Assisted Telemanipulation Tasks</title><description>In this work, we propose the generation of a
tube-shaped virtual fixture that guides the operator towards
a target position. This position is obtained through a HumanMachine Interface (HMI) and it is used to adapt the endpoint
of the virtual fixture by means of a reactive constraint-based
approach. In parallel, a target object is inferred in realtime through a Bayesian intent estimation algorithm that uses
information coming from a vision system and the HMI. A
shared control strategy is then used to attract the endpoint of
the virtual fixture towards the inferred target object. The path
of this reactive virtual fixture also adapts to avoid collisions
with dynamic obstacles. With our approach, we expect to
reduce the effort and fatigue of the operators when performing
telemanipulation tasks.</description><fulltext>true</fulltext><rsrctype>other</rsrctype><creationdate>2020</creationdate><recordtype>other</recordtype><sourceid>FZOIL</sourceid><recordid>eNqNzLEOgjAQgOEuDgZ9h9scjANWUEZjBFcNcW0ucJgLtZBeS3h8HXwAp3_58y3VvSJHHgO7FzwIm8ATwZN9iGihityiawhKnkP0JNANHs4iLIFaqMnSGx2P0X6BwUGN0stKLTq0QutfE7Upr_XltuujpTiRM62M2JBJ9_qQ5cdTYfIs10WqE7X97zRhDvp_9wPKCklQ</recordid><startdate>20200604</startdate><enddate>20200604</enddate><creator>Iregui Rincon, Santiago</creator><creator>Vergara, Cristian</creator><creator>De Schutter, Joris</creator><creator>Aertbeliën, Erwin</creator><scope>FZOIL</scope></search><sort><creationdate>20200604</creationdate><title>Generating Reactive Virtual Guidance Fixtures for Assisted Telemanipulation Tasks</title><author>Iregui Rincon, Santiago ; Vergara, Cristian ; De Schutter, Joris ; Aertbeliën, Erwin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-kuleuven_dspace_123456789_6563913</frbrgroupid><rsrctype>other</rsrctype><prefilter>other</prefilter><language>eng</language><creationdate>2020</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Iregui Rincon, Santiago</creatorcontrib><creatorcontrib>Vergara, Cristian</creatorcontrib><creatorcontrib>De Schutter, Joris</creatorcontrib><creatorcontrib>Aertbeliën, Erwin</creatorcontrib><collection>Lirias (KU Leuven Association)</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Iregui Rincon, Santiago</au><au>Vergara, Cristian</au><au>De Schutter, Joris</au><au>Aertbeliën, Erwin</au><format>book</format><genre>document</genre><ristype>GEN</ristype><title>Generating Reactive Virtual Guidance Fixtures for Assisted Telemanipulation Tasks</title><date>2020-06-04</date><risdate>2020</risdate><abstract>In this work, we propose the generation of a
tube-shaped virtual fixture that guides the operator towards
a target position. This position is obtained through a HumanMachine Interface (HMI) and it is used to adapt the endpoint
of the virtual fixture by means of a reactive constraint-based
approach. In parallel, a target object is inferred in realtime through a Bayesian intent estimation algorithm that uses
information coming from a vision system and the HMI. A
shared control strategy is then used to attract the endpoint of
the virtual fixture towards the inferred target object. The path
of this reactive virtual fixture also adapts to avoid collisions
with dynamic obstacles. With our approach, we expect to
reduce the effort and fatigue of the operators when performing
telemanipulation tasks.</abstract></addata></record> |
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| source | Lirias (KU Leuven Association) |
| title | Generating Reactive Virtual Guidance Fixtures for Assisted Telemanipulation Tasks |
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