{"id":1829,"date":"2019-04-14T16:18:48","date_gmt":"2019-04-14T06:18:48","guid":{"rendered":"https:\/\/www.cognav.net\/?p=1829"},"modified":"2019-04-14T16:18:48","modified_gmt":"2019-04-14T06:18:48","slug":"how-to-build-goal-directed-navigation-based-on-path-integration-and-decoding-of-grid-cells-in-an-artificial-neural-network%ef%bc%9f","status":"publish","type":"post","link":"https:\/\/braininspirednavigation.com\/?p=1829","title":{"rendered":"How to build goal-directed navigation based on path integration and decoding of grid cells in an artificial neural network\uff1f"},"content":{"rendered":"<p style=\"text-align: justify;\">Edvardsen, Vegard. &#8220;<a href=\"https:\/\/link.springer.com\/article\/10.1007\/s11047-016-9575-0\"><strong>Goal-directed navigation based on path integration and decoding of grid cells in an artificial neural network<\/strong><\/a>.&#8221; Natural Computing 18, no. 1 (2019): 13-27.<\/p>\n<p style=\"text-align: justify;\">The following content is extracted from Edvardsen 2019.<\/p>\n<p style=\"text-align: justify;\">Edvardsen, Vegard. &#8220;Goal-directed navigation based on path integration and decoding of grid cells in an artificial neural network.&#8221; Natural Computing 18, no. 1 (2019): 13-27.<\/p>\n<p style=\"text-align: justify;\">As neuroscience gradually uncovers how the brain represents and computes with high-level spatial information, the endeavor of constructing biologically-inspired robot controllers using these spatial representations has become viable. Grid cells are particularly interesting in this regard, as they are thought to provide a general coordinate system of space. <span style=\"color: red;\"><strong>Artificial neural network models of grid cells show the ability to perform path integration, but important for a robot is also the ability to calculate the direction from the current location, as indicated by the path integrator, to a remembered goal<\/strong><\/span>.<\/p>\n<p style=\"text-align: justify;\">This paper <span style=\"color: red;\"><strong>presents a neural system that integrates networks of path integrating grid cells with a grid cell decoding mechanism<\/strong><\/span>. <span style=\"color: red;\"><strong>The decoding mechanism detects differences between multiscale grid cell representations of the present location and the goal, in order to calculate a goal-direction signal for the robot.<\/strong><\/span> The model successfully guides a simulated agent to its goal, showing promise for implementing the system on a real robot in the future.<\/p>\n<p style=\"text-align: center;\"><img decoding=\"async\" src=\"https:\/\/www.braininspirednavigation.com\/wp-content\/uploads\/2019\/04\/041419_0552_Howtobuildg1.png\" alt=\"\" \/><\/p>\n<p style=\"text-align: center;\">The figure from Edvardsen 2019.<\/p>\n<p style=\"text-align: center;\"><img decoding=\"async\" src=\"https:\/\/www.braininspirednavigation.com\/wp-content\/uploads\/2019\/04\/041419_0552_Howtobuildg2.png\" alt=\"\" \/><\/p>\n<p style=\"text-align: center;\">The figure from Edvardsen 2019.<\/p>\n<p>&nbsp;<\/p>\n<p>For further info, please read the paper Edvardsen 2019.<\/p>\n<p>Edvardsen, Vegard. &#8220;<a href=\"https:\/\/link.springer.com\/article\/10.1007\/s11047-016-9575-0\"><strong>Goal-directed navigation based on path integration and decoding of grid cells in an artificial neural network<\/strong><\/a>.&#8221; Natural Computing 18, no. 1 (2019): 13-27.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Edvardsen, Vegard. &#8220;Goal-directed navigation based on path integration and decoding of grid cells in an artificial neural network.&#8221; Natural Computing 18, no. 1 (2019): 13-27. The following content is extracted from Edvardsen 2019. Edvardsen, Vegard. &#8220;Goal-directed navigation based on path integration and decoding of grid cells in an artificial neural network.&#8221; Natural Computing 18, no. [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[96,346,419],"tags":[460,103,461,292],"_links":{"self":[{"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts\/1829"}],"collection":[{"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1829"}],"version-history":[{"count":2,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts\/1829\/revisions"}],"predecessor-version":[{"id":1841,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts\/1829\/revisions\/1841"}],"wp:attachment":[{"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1829"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1829"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1829"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}