Multi-objective Intent-based Path Planning for Robots for Static and Dynamic Environments
This dissertation models human intent for a robot navigation task, managed by a human and undertaken by a robot in a dynamic, multi-objective environment. Intent is expressed by a human through a user interface and then translated into a robot trajectory that satisfies a set of human-specified obj...
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ndltd-BGMYU2-oai-scholarsarchive.byu.edu-etd-95102020-07-22T05:00:21Z Multi-objective Intent-based Path Planning for Robots for Static and Dynamic Environments Shaikh, Meher Talat This dissertation models human intent for a robot navigation task, managed by a human and undertaken by a robot in a dynamic, multi-objective environment. Intent is expressed by a human through a user interface and then translated into a robot trajectory that satisfies a set of human-specified objectives and constraints. For a goal-based robot navigation task in a dynamic environment, intent includes expectations about a path in terms of objectives and constraints to be met. If the planned path drifts from the human's intent as the environment changes, a new path needs to be planned. The intent framework has four elements: (a) a mathematical representation of human intent within a multi-objective optimization problem; (b) design of an interactive graphical user interface that enables a human to communicate intent to the robot and then to subsequently monitor intent execution; (c) integration and adoption of a fast online path-planning algorithms that generate solutions/trajectories conforming to the given intent; and (d) design of metric-based triggers that provide a human the opportunity to correct or adapt a planned path to keep it aligned with intent as the environment changes. Key contributions of the dissertation are: (i) design and evaluation of different user interfaces to express intent, (ii) use of two different metrics, cosine similarity and intent threshold margin, that help quantify intent, and (iii) application of the metrics in path (re)planning to detect intent mismatches for a robot navigating in a dynamic environment. A set of user studies including both controlled laboratory experiments and Amazon Mechanical Turk studies were conducted to evaluate each of these dissertation components. 2020-06-18T07:00:00Z text application/pdf https://scholarsarchive.byu.edu/etd/8510 https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=9510&context=etd https://lib.byu.edu/about/copyright/ Theses and Dissertations BYU ScholarsArchive Robot path-planning human-robot interaction multi-objective optimization human supervisory control user interfaces replanning intervention Physical Sciences and Mathematics |
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Robot path-planning human-robot interaction multi-objective optimization human supervisory control user interfaces replanning intervention Physical Sciences and Mathematics |
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Robot path-planning human-robot interaction multi-objective optimization human supervisory control user interfaces replanning intervention Physical Sciences and Mathematics Shaikh, Meher Talat Multi-objective Intent-based Path Planning for Robots for Static and Dynamic Environments |
description |
This dissertation models human intent for a robot navigation task, managed by a human and undertaken by a robot in a dynamic, multi-objective environment. Intent is expressed by a human through a user interface and then translated into a robot trajectory that satisfies a set of human-specified objectives and constraints. For a goal-based robot navigation task in a dynamic environment, intent includes expectations about a path in terms of objectives and constraints to be met. If the planned path drifts from the human's intent as the environment changes, a new path needs to be planned. The intent framework has four elements: (a) a mathematical representation of human intent within a multi-objective optimization problem; (b) design of an interactive graphical user interface that enables a human to communicate intent to the robot and then to subsequently monitor intent execution; (c) integration and adoption of a fast online path-planning algorithms that generate solutions/trajectories conforming to the given intent; and (d) design of metric-based triggers that provide a human the opportunity to correct or adapt a planned path to keep it aligned with intent as the environment changes. Key contributions of the dissertation are: (i) design and evaluation of different user interfaces to express intent, (ii) use of two different metrics, cosine similarity and intent threshold margin, that help quantify intent, and (iii) application of the metrics in path (re)planning to detect intent mismatches for a robot navigating in a dynamic environment. A set of user studies including both controlled laboratory experiments and Amazon Mechanical Turk studies were conducted to evaluate each of these dissertation components. |
author |
Shaikh, Meher Talat |
author_facet |
Shaikh, Meher Talat |
author_sort |
Shaikh, Meher Talat |
title |
Multi-objective Intent-based Path Planning for Robots for Static and Dynamic Environments |
title_short |
Multi-objective Intent-based Path Planning for Robots for Static and Dynamic Environments |
title_full |
Multi-objective Intent-based Path Planning for Robots for Static and Dynamic Environments |
title_fullStr |
Multi-objective Intent-based Path Planning for Robots for Static and Dynamic Environments |
title_full_unstemmed |
Multi-objective Intent-based Path Planning for Robots for Static and Dynamic Environments |
title_sort |
multi-objective intent-based path planning for robots for static and dynamic environments |
publisher |
BYU ScholarsArchive |
publishDate |
2020 |
url |
https://scholarsarchive.byu.edu/etd/8510 https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=9510&context=etd |
work_keys_str_mv |
AT shaikhmehertalat multiobjectiveintentbasedpathplanningforrobotsforstaticanddynamicenvironments |
_version_ |
1719329690961838080 |