Autonomous multi-vehicle contact reacquisition using feature-based navigation and in-situ adaptive path planning for AUVs
                                            conference paper
                                        
                                    
                                            The complexity and duration of search and identify missions in mine hunting operations with Unmanned Underwater Vehicles (UUVs) or Autonomous Underwater Vehicles (AUVs) increase as a result of vehicle position inaccuracies and limited communication. Consequently, reacquisition, where potential contacts need to be revisited for identification, becomes time consuming when using sensors with a small swath width. This paper focuses on decreasing the time required for reacquisition and identification by correcting for position errors on the identification vehicle. This is achieved by autonomously performing feature-based navigation and in-situ adaptive path planning with AUVs. Both the search AUV and the identification AUV automatically interpret side looking sonar data on-board to build maps of detected contacts and reference bathymetric features, or landmarks, during a mission. Feature position information is exchanged between the vehicles through underwater acoustic communication. The identification AUV performs in-situ, optimized path planning for reacquiring
potential threats detected by the search vehicle, while using the reference positions of the search vehicle for its navigation. This developed methodology has been implemented and experimentally validated with multiple heterogenous AUVs.
                                    potential threats detected by the search vehicle, while using the reference positions of the search vehicle for its navigation. This developed methodology has been implemented and experimentally validated with multiple heterogenous AUVs.
Topics
                                        
                                    TNO Identifier
                                        
                                            882321
                                        
                                    Publisher
                                        
                                            IEEE
                                        
                                    Source title
                                        
                                            OCEANS 2019 - Marseille, France, 2019
                                        
                                    Pages
                                        
                                            1-7
                                        
                                    Files
                                        
                                            
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