{"id":2598,"date":"2022-03-20T23:16:39","date_gmt":"2022-03-20T13:16:39","guid":{"rendered":"https:\/\/www.cognav.net\/?p=2598"},"modified":"2022-03-20T23:16:39","modified_gmt":"2022-03-20T13:16:39","slug":"how-to-enable-robots-navigate-based-on-experiences-and-predictive-map-inspired-by-spatial-cognition-in-the-brain","status":"publish","type":"post","link":"https:\/\/braininspirednavigation.com\/?p=2598","title":{"rendered":"How to enable robots navigate based on experiences and predictive map inspired by spatial cognition in the brain?"},"content":{"rendered":"<p style=\"text-align: justify;\">D. Liu, Z. Lyu, Q. Zou, X. Bian, M. Cong and Y. Du, &#8220;<a href=\"https:\/\/ieeexplore.ieee.org\/document\/9736961\">Robotic Navigation Based on Experiences and Predictive Map Inspired by Spatial Cognition<\/a>,&#8221; in IEEE\/ASME Transactions on Mechatronics, doi: 10.1109\/TMECH.2022.3155614.<\/p>\n<p style=\"text-align: justify;\">Abstract:<br \/>\n&#8220;Humans and animals have environmental cognition and navigation abilities. These abilities are closely related to the spatial cognitive mechanism of brain. <strong><span style=\"color: #ff0000;\">Based on this mechanism, we propose a novel robotic navigation framework based on experiences and predictive map inspired by spatial cognition to accurately construct environment experience and quickly plan path<\/span><\/strong>. The grid cell and the place cell are modeled to rapidly integrate self-motion cues. <strong><span style=\"color: #ff0000;\">The multidimensional grid coding and one-shot learning rule are utilized for activating the place representation of robot pose<\/span><\/strong>. Visual cues provide information for relocation. These information are integrated through experiences which express the topology of the environment, enabling the robot to accurately achieve spatial cognition of complex environment. <strong><span style=\"color: #ff0000;\">In order to realize the sequential decision making of hippocampus, the predictive map is introduced to quickly plan the experience sequence to target in dynamic environment.<\/span><\/strong> The successor representation model of robot&#8217;s state is constructed through reinforcement learning. <strong><span style=\"color: #ff0000;\">Combined with the goal-based reward function, the shortest path can be replanned to adapt to environment changes.<\/span> <\/strong>The proposed method is tested in simulated maze, Kitti dataset and corridor environment. Compared with other bionic navigation methods, it has a faster computing speed and higher precision with bionic characteristics. Compared with visual navigation methods, the navigation tasks can robustly be accomplished without complex system design.&#8221;<\/p>\n<p style=\"text-align: justify;\">D. Liu, Z. Lyu, Q. Zou, X. Bian, M. Cong and Y. Du, &#8220;<a href=\"https:\/\/ieeexplore.ieee.org\/document\/9736961\">Robotic Navigation Based on Experiences and Predictive Map Inspired by Spatial Cognition<\/a>,&#8221; in IEEE\/ASME Transactions on Mechatronics, doi: 10.1109\/TMECH.2022.3155614.<\/p>\n<p style=\"text-align: justify;\">\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"<p>D. Liu, Z. Lyu, Q. Zou, X. Bian, M. Cong and Y. Du, &#8220;Robotic Navigation Based on Experiences and Predictive Map Inspired by Spatial Cognition,&#8221; in IEEE\/ASME Transactions on Mechatronics, doi: 10.1109\/TMECH.2022.3155614. Abstract: &#8220;Humans and animals have environmental cognition and navigation abilities. These abilities are closely related to the spatial cognitive mechanism of brain. Based [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[126,114],"tags":[308,304,998,997],"_links":{"self":[{"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts\/2598"}],"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=2598"}],"version-history":[{"count":1,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts\/2598\/revisions"}],"predecessor-version":[{"id":2599,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts\/2598\/revisions\/2599"}],"wp:attachment":[{"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2598"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2598"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2598"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}