000007693 001__ 7693
000007693 005__ 20240531164756.0
000007693 02470 $$2doi$$a10.24868/issn.2515-818X.2020.052
000007693 035__ $$a4498263
000007693 037__ $$aGENERAL
000007693 245__ $$aTowards intelligent navigation in future autonomous surface vessels: developments, challenges and strategies
000007693 269__ $$a2020-10-05
000007693 336__ $$aConference Proceedings
000007693 520__ $$aThere is an increasing trend in developing autonomous surface vessels (ASVs) for a range of maritime activities including transportation, search and rescue and naval operations. Autonomy potentially offers economic benefits, reduced cost, increased operation efficiency and reduced risk. Autonomy means less reliance on human operators, replaced with intelligent decision-making systems. Currently, such intelligence is achieved using sophisticated autonomous navigation systems which may be considered as consisting of three core modules; namely the sensor and data acquisition system, the intelligent planning system, and the automatic control (auto-pilot) system. This paper discusses the state-of-the-art development with a particular interest in reliable and accurate environment awareness. Advantages of using key technologies such as filtering algorithms, fuzzy-logic and statistical learning in autonomous navigation for ASVs have been demonstrated and discussed.<br>
Future work also reflects intriguing insights in employing heterogenous sensory modules including LiDAR, radar and vision systems in next generation maritime autonomous navigation.
000007693 542__ $$fCC-BY-4.0
000007693 6531_ $$aautonomous surface vessels (ASVs)
000007693 6531_ $$aenvironment awareness
000007693 6531_ $$aadvance sensing technologies
000007693 6531_ $$aheterogenous sensory systems
000007693 7001_ $$aLiu, W$$uMarine Research Group, Department of Mechanical Engineering, University College London
000007693 7001_ $$aLiu, Y$$uMarine Research Group, Department of Mechanical Engineering, University College London
000007693 7001_ $$aSong, R$$uMarine Research Group, Department of Mechanical Engineering, University College London
000007693 7001_ $$aBucknall, R$$uMarine Research Group, Department of Mechanical Engineering, University College London
000007693 773__ $$tConference Proceedings of INEC
000007693 773__ $$jINEC 2020
000007693 789__ $$whttps://zenodo.org/record/4498263$$2URL$$eIsIdenticalTo
000007693 85641 $$uhttps://www.imarest.org/events/inec-2020$$yConference website
000007693 8564_ $$9fdc450c0-475b-4683-9667-e0f737db972d$$s3041265$$uhttps://library.imarest.org/record/7693/files/INEC_2020_Paper_84.pdf