{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:47:08Z","timestamp":1777657628590,"version":"3.51.4"},"reference-count":26,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Human. Robot."],"published-print":{"date-parts":[[2013,9]]},"abstract":"<jats:p> Biped humanoid robots have been developed to successfully perform human-like locomotion. Based on the use of well-developed locomotion control systems, humanoid robots are further expected to achieve high-level intelligence, such as vision-based obstacle avoidance navigation. To provide standard obstacle avoidance navigation problems for autonomous humanoid robot researches, the HuroCup League of Federation of International Robot-Soccer Association (FIRA) and the RoboCup Humanoid League defined the conditions and rules in competitions to evaluate the performance. In this paper, the vision-based obstacle avoidance navigation approaches for humanoid robots were proposed in terms of combining the techniques of visual localization, obstacle map construction and artificial potential field (APF)-based reactive navigations. Moreover, a small-size humanoid robot (HuroEvolution<jats:sup>JR<\/jats:sup>) and an adult-size humanoid robot (HuroEvolution<jats:sup>AD<\/jats:sup>) were used to evaluate the performance of the proposed obstacle avoidance navigation approach. The navigation performance was evaluated with the distance of ground truth trajectory collected from a motion capture system. Finally, the experiment results demonstrated the effectiveness of using vision-based localization and obstacle map construction approaches. Moreover, the APF-based navigation approach was capable of achieving smaller trajectory distance when compared to conventional just-avoiding-nearest-obstacle-rule approach. <\/jats:p>","DOI":"10.1142\/s0219843613500217","type":"journal-article","created":{"date-parts":[[2013,7,19]],"date-time":"2013-07-19T04:47:28Z","timestamp":1374209248000},"page":"1350021","source":"Crossref","is-referenced-by-count":4,"title":["VISION-BASED OBSTACLE AVOIDANCE NAVIGATION WITH AUTONOMOUS HUMANOID ROBOTS FOR STRUCTURED COMPETITION PROBLEMS"],"prefix":"10.1142","volume":"10","author":[{"given":"CHUNG-HSIEN","family":"KUO","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, R. O. 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