Advanced ROV Autonomy for Efficient Remote Control in the DexROV Project
Paolo Di Lillo, Enrico Simetti, Daniela De Palma, Elisabetta Cataldi, Giovanni Indiveri, Gianluca Antonelli, Giuseppe Casalino
- 发表年份
- 2016
- 引用次数
- 32
摘要
Abstract In this paper, we present DexROV, an EC Horizon 2020-funded project that proposes to implement novel operation strategies for underwater semiautonomous interventions. These costly and demanding operations are increasingly performed by remotely operated vehicles (ROVs), contributing to risk cutting for human divers. However, ROV operations require offshore structures, hosted on a support vessel with a crew of a significant amount of personnel necessary to properly handle and operate the robotic platform. One of the key goals of DexROV is to delocalize on shore the manned support as much as possible, reducing the crew onboard the support vessel and consequently the costs and risks of the whole operation. The control center is located onshore, far from the actual operation location. Operators interact with the ROV through a simulation environment that exploit 3D models of the environment built online relying on the perception and modeling capabilities of the robotic system and transmitted via satellite communication. Currently, ROVs lack the dexterous capabilities needed to perform many kinds of operations, for which human divers are still necessary. DexROV addresses this problem, equipping the ROV with two 6 DOF (degrees of freedom) dexterous manipulators with anthropomorphic end-effectors and providing semiautonomous capabilities. The control will rely on a multitask priority approach that will help the operator to focus on the main operation, leaving the low-level tasks to be autonomously performed by the ROV.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002