Intervention AUVs: The Next Challenge

详细信息    查看全文

• 作者：Pere Ridao^* ; ^{pere@eia.udg.ed" class="auth_mail" title="E-mail the corresponding author} ; Marc Carreras^* ; ^{marcc@eia.udg.ed" class="auth_mail" title="E-mail the corresponding author} ; David Ribas^* ; ^{dribas@eia.udg.ed" class="auth_mail" title="E-mail the corresponding author} ; Pedro J. Sanz^** ; ^{sanzp@uji.e" class="auth_mail" title="E-mail the corresponding author} ; Gabriel Oliver^*** ; ^{goliver@uib.e" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Autonomous Vehicles ; Robotic Manipulators ; Marine Systems
• 刊名：IFAC-PapersOnLine
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：47
• 期：3
• 页码：12146-12159
• 全文大小：1981 K

文摘

While commercially available AUVs are routinely used in survey missions, a new set of applications exists which clearly demand intervention capabilities. The maintenance of: permanent observatories underwater; submerged oil wells; cabled sensor networks; pipes; and the deployment and recovery of benthic stations are but a few of them. These tasks are addressed nowadays using manned submersibles or work-class ROVs, equipped with teleoperated arms under human supervision. Although researchers have recently opened the door to future I-AUVs, a long path is still necessary to pave the way to underwater intervention applications performed in an autonomous way. This paper reviews the evolution timeline in autonomous underwater intervention systems. Milestone projects in the state of the art are reviewed, highlighting their principal contributions to the field. To the best of the authors knowledge only three vehicles have demonstrated some autonomous intervention capabilities so far: ALIVE, SAUVIM and GIRONA 500 I-AUV. Next, GIRONA 500 I-AUV is presented and its software architecture discussed. Recent results in different scenarios are reported: 1) Valve turning and connector plugging/unplugging while docked to a sub-sea panel, 2) Free floating valve turning using learning by demonstration, and 3) Free floating multipurpose multisensory based object recovery. The paper ends discussing the lessons learned so far and presenting the authors view of the future.