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Robotic path planning for environmental field estimation and its application in aquatic monitoring

University of British Columbia

Recent advances in the technologies of sensing, robotics, and sensor networks have led to significant progress in environmental telemonitoring. Robotic systems have been widely developed and deployed in the field by using their capabilities of mobile sensing, autonomous navigation, and wireless communication. In particular, robotic monitoring and data sampling at locations of interest may be utilized to characterize and interpret the environmental phenomena of a study area. However, in real-world robotic sensing applications, the limitations of on-board resources will limit the coverage of the monitored area and the extent of acquired data, which will hinder the performance of field estimation and mapping. Meanwhile, the constraints of computational capability of the system components call for a computationally efficient framework to schedule and control the robotic sensing missions. This dissertation investigates and develops systematic sensor scheduling and path planning schemes for environmental field estimation through robotic sampling, and their application in aquatic monitoring. First, a hexagonal grid-based sampling frame is designed to distribute spatially balanced sampling locations over the monitored field. Two novel hexagonal grid-based survey planners are developed to generate energy-efficient sampling paths for the exploratory survey using mobile sensing robots, which can be executed in a computationally efficient manner. Second, an energy-constrained survey planner is developed, which achieves optimal coverage density for sampling, with a limit on the energy budget. The generated survey mission guides the robots to collect data samples for estimation and mapping of an unknown field under a Gaussian Process (GP) model. Third, a hierarchical planning framework with a built-in Gaussian Markov Random Field (GMRF) model is developed to provide informative path planning and adaptive sampling for efficient spatiotemporal monitoring. Fourth, the development of a cost-effective, rapidly deployable, and easily maintainable Wireless Mobile Sensor Network (WMSN) for on-line monitoring of surface water is presented. A novel On-Line Water Quality Indexing (OLWQI) scheme is developed and implemented to interpret the large volume of on-line measurements. The experimental results in the present dissertation demonstrate the effectiveness and efficiency of the proposed planning schemes and their application in aquatic environmental monitoring.

Text

2019-11-30

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/67743

Mechanical Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/