A group mobility model for ad hoc wireless networks
MSWiM '99 Proceedings of the 2nd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
Occupancy grids: a probabilistic framework for robot perception and navigation
Occupancy grids: a probabilistic framework for robot perception and navigation
Techniques for Deep Sea Near Bottom Survey Using an Autonomous Underwater Vehicle
International Journal of Robotics Research
Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics)
Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics)
Monte Carlo localization for mobile wireless sensor networks
Ad Hoc Networks
Target tracking based on a distributed particle filter in underwater sensor networks
Wireless Communications & Mobile Computing - Underwater Sensor Networks: Architectures and Protocols
Underwater SLAM in man-made structured environments
Journal of Field Robotics
Cooperative Localization for Autonomous Underwater Vehicles
International Journal of Robotics Research
Cooperative AUV Navigation using a Single Maneuvering Surface Craft
International Journal of Robotics Research
Underwater acoustic localization for small submersibles
Journal of Field Robotics
Wireless Underwater Communications
Wireless Personal Communications: An International Journal
Wireless Robotics: A Highly Promising Case for Standardization
Wireless Personal Communications: An International Journal
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Localization and mapping are the fundamental ability for underwater robots to carry out exploration and searching tasks autonomously. This paper presents a novel approach to localization and mapping of a school of wirelessly connected underwater robotic fish (URF). It is based on both Cooperative Localization Particle Filter (CLPF) scheme and Occupancy Grid Mapping Algorithm (OGMA). Using the probabilistic framework, the proposed CLPF has the major advantage that no prior knowledge about the kinematic model of URF is required to achieve accurate 3D localization. It works well when the number of mobile beacons is less than four, which is the minimum number for some traditional localization algorithms. The localization result of CLPF is fed into OGMA to build the environment map. The performance of the proposed algorithms is evaluated through extensive simulation experiments, and results verify the feasibility and effectiveness of the proposed strategy.