{"id":7051,"date":"2019-06-21T10:32:02","date_gmt":"2019-06-21T10:32:02","guid":{"rendered":"https:\/\/vicorob.udg.edu\/?p=7051"},"modified":"2019-06-21T10:32:02","modified_gmt":"2019-06-21T10:32:02","slug":"doctoral-thesis-advanced-underwater-vehicle-manipulation-through-real-time-motion-planning","status":"publish","type":"post","link":"https:\/\/vicorob.udg.edu\/ca\/doctoral-thesis-advanced-underwater-vehicle-manipulation-through-real-time-motion-planning\/","title":{"rendered":"DOCTORAL THESIS: Advanced Underwater Vehicle Manipulation through Real-Time Motion Planning"},"content":{"rendered":"

By Dina Nagui Youakim Isaac
\n<\/strong><\/p>\n

Supervised by Dr.\u00a0Pere Ridao<\/strong><\/p>\n

 <\/p>\n

 <\/p>\n

Abstract<\/strong><\/h3>\n

A key challenge in autonomous mobile manipulation is the ability to determine in real-time how to safely execute complex tasks when placed in an unknown world. Motion Planning has been widely used in terrestrial and aerial robots to cope with such challenges, while it stayed unexplored for underwater intervention. In the last few years, Intervention Autonomous Underwater Vehicles (I-AUVs) became subject of broad interest in research, with only few real demonstrations mostly relying on variations of the task-priority redundancy control framework.<\/p>\n

In response to those arising needs, this thesis focused on advancing the state of the art by investigating the use of Motion Planning to increase the autonomy of I-AUVs in the context of \u201cInspection, Maintenance, Repair\u201d missions in unknown environments.<\/p>\n

Through our work, we initially present a modeling and integration of our I-AUV using common terrestrial mobile manipulation framework MoveIt!, showing for the first time motion planning for an I-AUVs in the presence of virtual obstacles. Then, based on our observations of our previous demonstrations, and in order to base our choice of the motion planning technique on a solid scientific foundation, we performed a deep analysis of the state of the art motion planning techniques. We created benchmarks, and compared 17 motion planners in 5 different scenarios and came out with guidelines for choosing the best fitting method for given requirements. Later, we identified planner specifications for underwater intervention: 1) Real-Time response for a high Degree of Freedom (DoF) system, 2) Consistency, 3) Efficient trajectories in terms of traveled distance, safety, and system loose coupling utilization. As a consequence, we propose a new motion planning algorithm under the umbrella of search-based method, that exploits the loose coupling nature of an I- AUV while generating consistent, efficient, and safe trajectories in unknown environments.<\/p>\n

Both simulation and experimental (in water tanks) results are presented for various stages of the work, showing the flow and validating the efficiency and potential of the developed algorithm. The proposed method, conveniently integrated within the robot system\u2019s architecture, increases the reliability of the I-AUV performing intervention, both safely and robustly when operating in unknown terrains.<\/p>\n

 <\/p>\n

 <\/p>\n

Resum<\/strong><\/h3>\n

La capacitat de decidir en temps real com executar de manera segura uns tasca complexa en un entorn desconegut \u00e9s un repte clau en la manipulaci\u00f3 m\u00f3vil aut\u00f2noma. Per abordar-ho, s\u2019utilitzen habitualment t\u00e8cniques de Planificaci\u00f3 de Moviment tant en robots terrestres com aeris, mentre la seva aplicaci\u00f3 a l\u2019\u00e0mbit submar\u00ed roman inexplorada. Durant els darrers anys, l\u2019inter\u00e8s de la comunitat cient\u00edfica pels I-AUVs ha crescut significativament, havent fructificat les primeres demostracions experimentals basades en variacions del m\u00e8tode de control de redund\u00e0ncia utilitzant tasques amb prioritat. Aquesta tesi doctoral avan\u00e7a l\u2019estat de l\u2019art investigant l\u2019\u00fas dels m\u00e8todes de Planificaci\u00f3 de Moviment per augmentar l\u2019autonomia dels I-AUVs per aplicacions d\u2019Inspecci\u00f3, Manteniment i Reparaci\u00f3 executades en entorns desconeguts. A trav\u00e9s del nostre treball, presentem la modelitzaci\u00f3 i integraci\u00f3 del nostre I-AUV en MoveIt!, un entorn per a la programaci\u00f3 d\u2019aplicacions de manipulaci\u00f3 m\u00f3vil comunament utilitzat en rob\u00f3tica terrestre.<\/p>\n

Amb l\u2019objectiu de fonamentar cient\u00edficament l\u2019elecci\u00f3 del m\u00e8tode de Planificaci\u00f3 de Moviment apropiat al nostre problema, s\u2019ha dut a terme un an\u00e0lisis comparatiu de l\u2019estat de l\u2019art. S\u2019han definit 5 escenaris de manipulaci\u00f3 representatius (benchmarks) i s\u2019han comparat 17 planificadors diferents. L\u2019an\u00e0lisis dels resultats ens ha perm\u00e8s establir les guies per a l\u2019elecci\u00f3 de la t\u00e8cnica m\u00e9s apropiada a les nostres necessitats. Posteriorment, s\u2019han identificat les especificacions desitjades pels planificadors en aplicacions d\u2019intervenci\u00f3 submarina: 1) Resposta a temps real d\u2019un sistema amb un elevat nombre de graus de llibertat, 2) Consist\u00e8ncia 3) Generaci\u00f3 de traject\u00f2ries eficients en termes de distancia i seguretat, aix\u00ed com l\u2019\u00fas de sistemes d\u00e8bilment acoblats. A partir dels resultats de l\u2019an\u00e0lisis, es proposa un nou algoritme de planificaci\u00f3 de moviment, dintre de la familia dels m\u00e8todes de cerca, que explota l\u2019acoblament d\u00e9bil entre el manipulador i el vehicle, generant, al mateix temps, traject\u00f2ries consistents, eficients i segures en entorns desconeguts. Al llarg de la recerca duta a terme s\u2019han utilitzat resultats en simulaci\u00f3 i experimentals (en tanc d\u2019aigua), per a validar l\u2019efici\u00e8ncia i el potencial de l\u2019algoritme. El m\u00e8tode proposat, convenientment integrat en el sistema de control, incrementa la fiabilitat del robot que desenvolupa la intervenci\u00f3, millorant la seguretat i robustesa operant en un entorn desconegut.<\/p>\n

 <\/p>\n

Online video:\u00a0https:\/\/bit.ly\/2qMWc9d<\/a><\/p>\n

 <\/p>\n

\"\"<\/p>\n","protected":false},"excerpt":{"rendered":"

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