<?xml version="1.0" encoding="UTF-8"?>

<?xml-stylesheet type="text/xsl" href="/static/oaitohtml.xsl"?>

<!--
<?xml-stylesheet type="text/xsl" href="/oaitohtml.xsl"?>
-->

<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <responseDate>2026-10-14T17:46:30Z</responseDate>
    <request verb="GetRecord" metadataPrefix="oai_dc" identifier="10.57760/sciencedb.010jp" >https://www.scidb.cn/oai</request>
<GetRecord>
    <record>
    <header >
    <identifier>10.57760/sciencedb.010jp</identifier>
    <datestamp>2026-08-28T10:27:04Z</datestamp>
</header>
    <metadata>
        
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:date>2026-08-28</dc:date>
  <dc:title>Adaptive Distance Kicking Strategy for Humanoid Robots Based on Prior Trajectory Guidance and Multi-Task Residual Learning</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.010jp</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The data were obtained from experiments conducted in the RoboCup 3D official platform SimSpark, starting in March 2026.&amp;nbsp;&amp;nbsp;Table 3 presents the keyframe action data as well as the kicking accuracy and time required to kick the ball under the proposed method for both stationary and rolling balls.&amp;nbsp;&amp;nbsp;Figure 7 shows the training reward curves comparing Baseline A and the hybrid residual control method.&amp;nbsp;&amp;nbsp;KickBall.mp4 is the demonstration video of the proposed method.Figure 8 shows the training reward curves of the hybrid residual control method.&amp;nbsp;&amp;nbsp;Figure 9 shows the training reward curves of the proposed method.&amp;nbsp;&amp;nbsp;Figures 10 and 11 present the kicking distance errors obtained from testing the proposed method.</dc:description>
  <dc:subject>humanoid robot; robot soccer; residual learning; deep reinforcement learning; hybrid control</dc:subject>
  <dc:creator>Dou Aobo</dc:creator>
  <dc:creator>Liu Fei</dc:creator>
  <dc:creator>Yang Hongyong</dc:creator>
  <dc:creator>Liu Li</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
</oai_dc:dc>

    </metadata>
</record>
</GetRecord>
</OAI-PMH>