Project Details
Projekt
Decentralized Cooperative Exploration of Nonstationary Spatiotemporal Environmental Fields with Autonomous Underwater Vehicle Systems
Applicant
Professor Dr.-Ing. Edwin Kreuzer
Subject Area
Automation, Mechatronics, Control Systems, Intelligent Technical Systems, Robotics
Term
from 2017 to 2023
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 357117608
Systems for environmental field estimation are of great interest because they allow data collection in oceanographic research, locating pollution sources, and analyzing flow fields at offshore wind farms. Usually, stationary sensors are installed for such tasks. However, a group of Autonomous Underwater Vehicles (AUVs) can achieve a higher spatial resolution due to possible sensor repositioning. While mobile sensor networks controlled by a central unit can achieve great performance and are already investigated in great depth, decentralized approaches are often favored in underwater scenarios where vehicles cannot communicate with a central unit regularly, because communication channels are unreliable and of low bandwidth. The development of truly decentralized multi-AUV systems requires extensions beyond the state of the art.A group of AUVs deployed into a marine environment performing distributed spatiotemporal estimation tasks is considered in this research project. The AUVs take measurements of dynamic physical processes which are modelled as non-stationary Gaussian random fields. The fields describe the evolution of quantities such as water temperature or concentration of pollutants. The covariance of the Gaussian random field is used for decentralized coordination of the AUV group based on synchronization and path integral control. An approach based on synchronization and path integral control enables decentralized environmental exploration. Since the unknown fields are modeled by a nonparametric approach (Gaussian processes) a minimum of a priori knowledge is required. The initially unknown covariance function can be estimated along the field. The approach allows analyzing a fundamental tradeoff in explorative problems which is summarized by the following question: Shall future observations be collected to improve the field model (a better covariance function estimate), or shall observations be taken at locations where the current (possibly inaccurate) model indicates the highest uncertainty?The Institute of Mechanics and Ocean Engineering has in recent years conducted and published research on both theoretical and practical aspects of AUV dynamics and controls. Algorithms for centrally controlled AUV groups for exploring environmental fields have been derived which are modeled with physics-based approaches. Micro AUVs have been developed. These results are the starting point for developing a truly decentralized controls framework for exploration. Furthermore, preliminary studies on combining field uncertainty with decentralized coordination control have been conducted. Further studies show that a vehicle can explore an advection-diffusion field where the field belief is represented by a Gaussian Markov random field.The verification of the concept will be conducted experimentally. With the developed controls framework, a group of micro-AUVs will perform tasks such as level curve tracking, gradient climbing and source localization.
DFG Programme
Research Grants
International Connection
Brazil, USA
