{"id":753,"date":"2022-04-04T14:05:21","date_gmt":"2022-04-04T05:05:21","guid":{"rendered":"http:\/\/www.sawada.phys.waseda.ac.jp\/?page_id=753"},"modified":"2024-10-02T09:47:29","modified_gmt":"2024-10-02T00:47:29","slug":"%e3%83%a1%e3%83%b3%e3%83%90%e3%83%bc-%e7%b9%94%e5%b1%b1-%e3%81%bf%e3%81%aa%e5%ad%90","status":"publish","type":"page","link":"https:\/\/www.sawada.phys.waseda.ac.jp\/?page_id=753","title":{"rendered":"\u30e1\u30f3\u30d0\u30fc | \u7e54\u5c71 \u307f\u306a\u5b50"},"content":{"rendered":"

\u81ea\u5f8b\u578b\u79fb\u52d5\u30ed\u30dc\u30c3\u30c8\u306b\u304a\u3051\u308b\u4eba\u9593\u4e3b\u5c0e\u306e\u8ee2\u79fb\u5b66\u7fd2\u624b\u6cd5<\/strong>
\nHuman-Guided Transfer Learning Method for Autonomous Mobile Robots<\/strong><\/p>\n

\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306f\u591a\u304f\u306e\u5fdc\u7528\u5206\u91ce\u3067\u512a\u308c\u305f\u6210\u679c\u3092\u4e0a\u3052\u3066\u3044\u307e\u3059\u304c\u3001\u305d\u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u306b\u306f\u591a\u5927\u306a\u6642\u9593\u3068\u81a8\u5927\u306a\u30c7\u30fc\u30bf\u304c\u5fc5\u8981\u3067\u3042\u308a\u3001\u7279\u306b\u7269\u7406\u7684\u306a\u74b0\u5883\u3067\u52d5\u4f5c\u3059\u308b\u81ea\u5f8b\u30ed\u30dc\u30c3\u30c8\u306b\u304a\u3044\u3066\u3001\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u3067\u306e\u5b66\u7fd2\u304c\u56f0\u96e3\u306a\u554f\u984c\u3068\u306a\u308a\u307e\u3059\u3002\u3053\u306e\u554f\u984c\u3092\u89e3\u6c7a\u3059\u308b\u305f\u3081\u306b\u3001\u672c\u7814\u7a76\u3067\u306f\u3001\u8ee2\u79fb\u5b66\u7fd2\u3092\u7528\u3044\u305f\u30d2\u30e5\u30fc\u30de\u30f3\u30fb\u30a4\u30f3\u30fb\u30b6\u30fb\u30eb\u30fc\u30d7\uff08Human-in-the-Loop: HITL\uff09\u3068\u3044\u3046\u30a2\u30d7\u30ed\u30fc\u30c1\u3092\u63d0\u6848\u3057\u3066\u3044\u307e\u3059\u3002
\n\u65e2\u5b58\u306e\u77e5\u8b58\u3092\u4ed6\u306e\u9818\u57df\u306b\u9069\u7528\u3059\u308b\u8ee2\u79fb\u5b66\u7fd2\u306e\u6982\u5ff5\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u4eba\u9593\u306e\u77e5\u8b58\u3084\u76f4\u611f\u3092\u30ed\u30dc\u30c3\u30c8\u306e\u5b66\u7fd2\u904e\u7a0b\u306b\u76f4\u63a5\u7d44\u307f\u8fbc\u3080HITL\u306e\u67a0\u7d44\u307f\u3092\u63d0\u6848\u3057\u3001\u30ed\u30dc\u30c3\u30c8\u304c\u4eba\u9593\u306e\u5e38\u8b58\u3084\u5c02\u9580\u77e5\u8b58\u3092\u6d3b\u7528\u3057\u3066\u5b66\u7fd2\u306e\u53ce\u675f\u3092\u65e9\u3081\u308b\u3053\u3068\u3092\u76ee\u6307\u3057\u307e\u3059\u3002\u7279\u306b\u3001\u4eba\u9593\u306e\u5224\u65ad\u3084\u8a55\u4fa1\u3092\u5c0e\u5165\u3059\u308b\u3053\u3068\u3067\u3001\u30ed\u30dc\u30c3\u30c8\u306e\u6a5f\u68b0\u5b66\u7fd2\u80fd\u529b\u3068\u4eba\u9593\u306e\u76f4\u611f\u306e\u30ae\u30e3\u30c3\u30d7\u3092\u57cb\u3081\u3001\u8907\u96d1\u306a\u73fe\u5b9f\u4e16\u754c\u306e\u30b7\u30ca\u30ea\u30aa\u3067\u3088\u308a\u52b9\u7387\u7684\u304b\u3064\u9069\u5fdc\u529b\u306e\u3042\u308b\u81ea\u5f8b\u30ed\u30dc\u30c3\u30c8\u5b66\u7fd2\u306e\u5b9f\u73fe\u3092\u56f3\u308a\u307e\u3059\u3002
\n\u672c\u7814\u7a76\u3067\u306f\u3001\u885d\u7a81\u56de\u907f\u5b66\u7fd2\u3092\u5bfe\u8c61\u3068\u3057\u305f\u4e00\u9023\u306e\u5b9f\u9a13\u3092\u901a\u3058\u3066\u3001\u4e8b\u524d\u77e5\u8b58\u306e\u6709\u7121\u3084\u7570\u306a\u308b\u5b9f\u9a13\u74b0\u5883\u304c\u30ed\u30dc\u30c3\u30c8\u306e\u5b66\u7fd2\u52b9\u7387\u306b\u4e0e\u3048\u308b\u5f71\u97ff\u3092\u4f53\u7cfb\u7684\u306b\u8a55\u4fa1\u3057\u307e\u3057\u305f\u3002<\/p>\n

\u5b9f\u9a13\u306e\u69d8\u5b50<\/a><\/p>\n

Neural networks have demonstrated remarkable success across various fields of application; however, their training requires substantial time and vast amounts of data, which poses a significant challenge, particularly for autonomous robots operating in physical environments where real-time learning is difficult. To address this issue, this study proposes an approach based on Human-in-the-Loop (HITL) learning, utilizing transfer learning.
\nBy leveraging the concept of transfer learning, which applies existing knowledge to new domains, we propose a HITL framework that directly incorporates human knowledge and intuition into the robot\u2019s learning process. The goal is to accelerate the convergence of the robot’s learning by utilizing human common sense and domain-specific expertise. In particular, by integrating human judgment and evaluation, we aim to bridge the gap between the robot\u2019s machine learning capabilities and human intuition, enabling more efficient and adaptable autonomous robot learning in complex, real-world scenarios.
\nIn this study, we systematically evaluate the impact of prior knowledge and varying experimental conditions on the learning efficiency of robots, focusing on collision avoidance learning through a series of experiments.<\/p>\n

Video of the experiments<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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