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Tham khảo tài liệu 'field and service robotics - corke p. and sukkarieh s.(eds) part 2', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Visual Motion Estimation for an Autonomous Underwater Reef Monitoring Robot Matthew Dunbabin Kane Usher and Peter Corke CSIRO ICT Centre PO Box 883 Kenmore QLD 4069 Australia Summary. Performing reliable localisation and navigation within highly unstructured underwater coral reef environments is a difficult task at the best of times. Typical research and commercial underwater vehicles use expensive acoustic positioning and sonar systems which require significant external infrastructure to operate effectively. This paper is focused on the development of a robust vision-based motion estimation technique using low-cost sensors for performing real-time autonomous and untethered environmental monitoring tasks in the Great Barrier Reef without the use of acoustic positioning. The technique is experimentally shown to provide accurate odometry and terrain profile information suitable for input into the vehicle controller to perform a range of environmental monitoring tasks. 1 Introduction In light of recent advances in computing and energy storage hardware Autonomous Underwater Vehicles AUVs are emerging as the next viable alternative to human divers for remote monitoring and survey tasks. There are a number of remotely operated ROV and AUVs performing various monitoring tasks around the world 17 . These vehicles are typically large and expensive require considerable external infrastructure for accurate positioning and need more than one person to operate a single vehicle. These vehicles also generally avoid the highly unstructured reef environments such as Australia s Great Barrier Reef with limited research performed on shallow water applications and reef traversing. Where surveying at greater depths is required ROV s have been used for video transects and biomass identification however these vehicles still require the human operator in the loop. Knowing the position and distance a AUV has moved is critical to ensure that correct and repeatable measurements are being .