Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.600219
Title: Developing a holonomic iROV as a tool for kelp bed mapping
Author: Williamson, Benjamin
Awarding Body: University of Bath
Current Institution: University of Bath
Date of Award: 2013
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Abstract:
Kelp beds support a vast and diverse ecosystem including marine mammals, fish, invertebrates, other algae and epibiota, yet these kelp beds can be highly ephemeral. Mapping the density and distribution of kelp beds, and assessing change over yearly cycles, are important objectives for coastal oceanography. However, nearshore habitat mapping is challenging, affected by dynamic currents, tides, shallow depths, frequent non-uniform obstacles and often turbid water. Noisy and often incomplete sensor data compound a lack of landmarks available for navigation. The intelligent, position-aware holonomic ROV (iROV) SeaBiscuit was designed specifically for this nearshore habitat mapping application and represents a novel synthesis of techniques and innovative solutions to nearshore habitat mapping. The concept of an iROV combines the benefits of autonomous underwater navigation and mapping while maintaining the flexibility and security of remote high-level control and supervision required for operation in hostile, complex underwater environments. An onboard battery provides an energy buffer for high-powered thrust and security of energy supply. Onboard low-level autonomy provides robust autopilot features, including station-keeping or course-holding in a flow, allowing the operator to direct the survey and supervise mapping data in realtime during acquisition. With the aim of providing high-usability maps on a budget feasible for small-scale field research groups, SeaBiscuit fuses the data from an orthogonal arrangement of a forward-facing multibeam sonar and a complementary 360° scanning sonar with a full navigation suite to explore and map the nearshore environment. Sensor fusion, coupled with the holonomic propulsion system, also allows optimal use of the information available from the limited budget sensor suite. Robust and reliable localisation is achieved even with noisy and incomplete sensor data using a relatively basic Inertial Navigation System and sonar-aided SLAM in the absence of an expensive Doppler velocity log or baseline navigation system. Holonomic motion in the horizontal plane and an axisymmetric hull provide the manoeuvrability required to operate in this complex environment, while allowing 3D maps to be generated in-transit. The navigation algorithms were tested mapping a piling dock and the habitat mapping sensors calibrated using an ‘artificial’ kelp bed of manually dimensioned kelp stipes transplanted to a sheltered but open-water real-world environment. Sea trials demonstrated mapping open ocean kelp beds, identifying clusters of stipes, converting this into a useful measure of biomass and generating a density surface across the kelp bed. This research provides field-proven techniques to improve the nearshore habitat mapping capabilities of underwater vehicles. Future work includes the transition to full-scale kelp bed mapping, and further development of the vehicle and sensor fusion algorithms to improve nearshore navigation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.600219  DOI: Not available
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