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Active Pose SLAM
We present an active exploration strategy that complements Pose SLAM [1] and optimal navigation in Pose SLAM [2]. The method evaluates the utility of exploratory and place revisiting sequences and chooses the one that minimizes overall map and path entropies. The technique considers trajectories of...
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creator | Valencia, R. Miro, J. V. Dissanayake, G. Andrade-Cetto, J. |
description | We present an active exploration strategy that complements Pose SLAM [1] and optimal navigation in Pose SLAM [2]. The method evaluates the utility of exploratory and place revisiting sequences and chooses the one that minimizes overall map and path entropies. The technique considers trajectories of similar path length taking marginal pose uncertainties into account. An advantage of the proposed strategy with respect to competing approaches is that to evaluate information gain over the map, only a very coarse prior map estimate needs to be computed. Its coarseness is independent and does not jeopardize the Pose SLAM estimate. Moreover, a replanning scheme is devised to detect significant localization improvement during path execution. The approach is tested in simulations in a common publicly available dataset comparing favorably against frontier based exploration. |
doi_str_mv | 10.1109/IROS.2012.6385637 |
format | conference_proceeding |
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V. ; Dissanayake, G. ; Andrade-Cetto, J.</creator><creatorcontrib>Valencia, R. ; Miro, J. V. ; Dissanayake, G. ; Andrade-Cetto, J.</creatorcontrib><description>We present an active exploration strategy that complements Pose SLAM [1] and optimal navigation in Pose SLAM [2]. The method evaluates the utility of exploratory and place revisiting sequences and chooses the one that minimizes overall map and path entropies. The technique considers trajectories of similar path length taking marginal pose uncertainties into account. An advantage of the proposed strategy with respect to competing approaches is that to evaluate information gain over the map, only a very coarse prior map estimate needs to be computed. Its coarseness is independent and does not jeopardize the Pose SLAM estimate. Moreover, a replanning scheme is devised to detect significant localization improvement during path execution. 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Moreover, a replanning scheme is devised to detect significant localization improvement during path execution. The approach is tested in simulations in a common publicly available dataset comparing favorably against frontier based exploration.</description><subject>Collision avoidance</subject><subject>Entropy</subject><subject>Simultaneous localization and mapping</subject><subject>Trajectory</subject><subject>Uncertainty</subject><issn>2153-0858</issn><issn>2153-0866</issn><isbn>1467317373</isbn><isbn>9781467317375</isbn><isbn>9781467317351</isbn><isbn>1467317365</isbn><isbn>9781467317368</isbn><isbn>1467317357</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo9j8FKAzEQQKe2grUueBUv_YFdM5lkkj0updrClhar55ImE1hRlG4R_HsFq6d3ePDgAdygqhBVfbd8XG8rrVBXTN4yuQEUtfNo2BE6sngGY42WSuWZh3D5JxyN_oX1F1D0_YtS6qfJhPUYrpt47D5lunnvZbptm9UVnOfw2ktx4gSe7-dPs0XZrh-Ws6Yto2Z1LE1KyWgyibPNWsccYiJUxhiyjBKIAu9T3EcfrU0eUXIwRBJMcCk6RxO4_e12IrL7OHRv4fC1O83RNzSsPBI</recordid><startdate>20120101</startdate><enddate>20120101</enddate><creator>Valencia, R.</creator><creator>Miro, J. 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V.</creatorcontrib><creatorcontrib>Dissanayake, G.</creatorcontrib><creatorcontrib>Andrade-Cetto, J.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore Digital Library</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Valencia, R.</au><au>Miro, J. V.</au><au>Dissanayake, G.</au><au>Andrade-Cetto, J.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Active Pose SLAM</atitle><btitle>2012 IEEE/RSJ International Conference on Intelligent Robots and Systems</btitle><stitle>IROS</stitle><date>2012-01-01</date><risdate>2012</risdate><spage>1885</spage><epage>1891</epage><pages>1885-1891</pages><issn>2153-0858</issn><eissn>2153-0866</eissn><isbn>1467317373</isbn><isbn>9781467317375</isbn><eisbn>9781467317351</eisbn><eisbn>1467317365</eisbn><eisbn>9781467317368</eisbn><eisbn>1467317357</eisbn><abstract>We present an active exploration strategy that complements Pose SLAM [1] and optimal navigation in Pose SLAM [2]. The method evaluates the utility of exploratory and place revisiting sequences and chooses the one that minimizes overall map and path entropies. The technique considers trajectories of similar path length taking marginal pose uncertainties into account. An advantage of the proposed strategy with respect to competing approaches is that to evaluate information gain over the map, only a very coarse prior map estimate needs to be computed. Its coarseness is independent and does not jeopardize the Pose SLAM estimate. Moreover, a replanning scheme is devised to detect significant localization improvement during path execution. The approach is tested in simulations in a common publicly available dataset comparing favorably against frontier based exploration.</abstract><pub>IEEE</pub><doi>10.1109/IROS.2012.6385637</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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ispartof | 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012, p.1885-1891 |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Collision avoidance Entropy Simultaneous localization and mapping Trajectory Uncertainty |
title | Active Pose SLAM |
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