Experimental validation of a velocity obstacle based collision avoidance algorithm for unmanned surface vehicles

Cho, Yong-Hoon; Han, Jungwook; Kim, Jinwhan; Lee, Phil-Yeob; Park, Shin-Bae

doi:10.1016/j.ifacol.2019.12.328

Cited by 25 publications

(9 citation statements)

References 10 publications

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“…To ensure that the USV follows a path with a small cross‐track error (CTE), steering and speed control were introduced. In the case of steering, the waterjet nozzle angle command

{\delta }_{{\rm{c}}}

was determined based on the lookahead‐based steering method with the LOS and pure pursuit (PP) guidance laws (Cho et al, 2019; Fossen, 2011; Yun et al, 2015). The descriptions of the steering method are provided in Figure 13.…”

Section: Extended Autonomous Navigation Algorithmsmentioning

confidence: 99%

Field demonstration of advanced autonomous navigation technique for a fully unmanned surface vehicle in complex coastal traffic areas

Han¹,

Park²,

Park³

et al. 2023

Journal of Field Robotics

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This study introduces an advanced autonomous navigation algorithm for unmanned surface vehicle (USV) operations in complex coastal traffic areas. To facilitate the undertaking of tests for innovative technologies, the Korean government has designated regulation‐free special zones, thereby enabling field tests for USV demonstrations without an onboard safety person on real manned‐ship navigation routes. To enable real‐world USV operation without onboard safety person, an existing autonomous navigation algorithm is extended to achieve sufficiently reliable and robust USV operation. Accordingly, berthing and unberthing algorithms are newly developed for unmanned operation, and enhanced situational awareness algorithms are applied to detect all types of obstacles, including small‐sized floating objects spread over a wide range, such as a fish farm. In particular, the Korean intelligent maritime transportation service, called e‐Navigation, is incorporated into the autonomous navigation algorithms to overcome the limitations of vehicle autonomy based on onboard sensors. To demonstrate the capability of fully unmanned operation in real marine traffic scenarios, long‐distance navigation (54 km on a single voyage) was conducted by running several missions, including navigation in complex fish farm areas, maritime surveys, collision avoidance, navigation on real traffic routes, and emergency response. The extended navigation algorithms and results of the field tests are presented and discussed in this paper.

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“…To ensure that the USV follows a path with a small cross‐track error (CTE), steering and speed control were introduced. In the case of steering, the waterjet nozzle angle command

{\delta }_{{\rm{c}}}

Section: Extended Autonomous Navigation Algorithmsmentioning

confidence: 99%

Field demonstration of advanced autonomous navigation technique for a fully unmanned surface vehicle in complex coastal traffic areas

Han¹,

Park²,

Park³

et al. 2023

Journal of Field Robotics

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“…Currently, SIA is attracting growing attention in unmanned ship collision avoidance, as illustrated by recent relevant papers (e.g. Woo and Kim, 2020;Cho et al, 2019;Wang et al, 2020 andShen et al, 2019).…”

Section: Geometric Collision Modelsmentioning

confidence: 99%

Geometrical risk evaluation of the collisions between ships and offshore installations using rule-based Bayesian reasoning

Liu

Yang

et al. 2021

Reliability Engineering & System Safety

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“…S HIPS navigating in open waters are obliged to comply with the international regulations for preventing collisions at sea (COLREGs), which correspond to the traffic laws of public roads [1]. The COLREGs, adopted by the international maritime organization (IMO), contain various rules for maritime traffic safety, such as the light and sound signals for communications and guidelines on vessel priority [2]- [4]. In particular, the regulations provide a conflict resolution procedure to resolve encounters between ships.…”

Section: Introductionmentioning

confidence: 99%

Intent Inference of Ship Collision Avoidance Behavior Under Maritime Traffic Rules

Cho

Kim

2021

IEEE Access

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This paper proposes an algorithm to infer the maneuver intention of an obstacle ship and to check its compliance with the maritime traffic rules to avoid ship collision and ensure maritime traffic safety. A probabilistic graphical model is constructed to represent the relationship between motion observations of the obstacle ship and its hidden maneuver intention to comply with the traffic rules. The probabilistic belief of the ship's intention is modeled and quantified using probabilistic tools such as dynamic Bayesian networks. Three different intent inference models are formulated considering the different levels of observation configurations, and their calculation procedures are described. To demonstrate the feasibility of the proposed intent inference algorithm, Monte-Carlo simulations were conducted and the results are presented.

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Experimental validation of a velocity obstacle based collision avoidance algorithm for unmanned surface vehicles

Cited by 25 publications

References 10 publications

Field demonstration of advanced autonomous navigation technique for a fully unmanned surface vehicle in complex coastal traffic areas

Field demonstration of advanced autonomous navigation technique for a fully unmanned surface vehicle in complex coastal traffic areas

Geometrical risk evaluation of the collisions between ships and offshore installations using rule-based Bayesian reasoning

Intent Inference of Ship Collision Avoidance Behavior Under Maritime Traffic Rules

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