COLREGs-Compliant Unmanned Surface Vehicles Collision Avoidance Based on Multi-Objective Genetic Algorithm

Ning, Jun; Chen, Hanmin; Li, Tieshan; Li, Wei; Li, Chunze

doi:10.1109/access.2020.3030262

Cited by 40 publications

(20 citation statements)

References 43 publications

(59 reference statements)

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“… Burmeister et al (2015) ; Johansen et al (2016a) ; Johansen et al (2016b) ; Kufoalor et al (2019) described a direct link between the controller and the onboard auto- or track pilot. Instead, Ning (2018) ; Eriksen et al (2019) , Beser and Yildirim (2018) ; Meyer et al (2020) ; Ning et al (2020) ; Penttinen (2020) assumed direct access to the engine order telegraph (EOT) and rudder control. Burmeister et al (2015) also described a human readable recommendation system besides the track pilot link.…”

Section: Resultsmentioning

confidence: 99%

“…Naturally, dynamic own ship data has also been used by all approaches, even though sometimes the approaches did only rely on relative values and not on a position in a global reference frame, as e.g., in Naeem et al (2016) . Additionally, differentiation between Speed over Ground and Speed through Water has not been considered in all cases or has not been specified in detail, as e.g., in Hu et al (2017) ; Beser and Yildirim (2018) ; Ning et al (2020) . Indeed, one-third of the approaches relied on ship-specific maneuvering models, requiring more detailed position and velocity data in at least three degrees of freedom (surge, sway, and yaw) to function.…”

Section: Resultsmentioning

confidence: 99%

“…Besides a wide variety of approaches published on maritime collision avoidance, it must be noted that most approaches in science do often only cover and discuss approaches regarding the basic rules regarding Overtaking (R13), Head-on encounter (R14) and Crossing (R16) as well as the associated rules regarding Give-way (R16) and Stand-on obligations (R17), and are thus only covering collision avoidance situation in sight of each other. Some papers, i.e., Burmeister et al (2015) ; Johansen et al (2016a) ; Johansen et al (2016b) ; Hu et al (2017) ; Eriksen et al (2019) , Eriksen and Breivik (2019) ; Kufoalor et al (2019) ; Kufoalor et al (2020) ; Ning et al (2020) ; Penttinen (2020) also developed approaches to address the need for an observable maneuver (R8).…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Autonomous Collision Avoidance at Sea: A Survey

Burmeister

Constapel

2021

Front. Robot. AI

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In this survey, results from an investigation on collision avoidance and path planning methods developed in recent research are provided. In particular, existing methods based on Artificial Intelligence, data-driven methods based on Machine Learning, and other Data Science approaches are investigated to provide a comprehensive overview of maritime collision avoidance techniques applicable to Maritime Autonomous Surface Ships. Relevant aspects of those methods and approaches are summarized and put into suitable perspectives. As autonomous systems are expected to operate alongside or in place of conventionally manned vessels, they must comply with the COLREGs for robust decision-support/-making. Thus, the survey specifically covers how COLREGs are addressed by the investigated methods and approaches. A conclusion regarding their utilization in industrial implementations is drawn.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Autonomous Collision Avoidance at Sea: A Survey

Burmeister

Constapel

2021

Front. Robot. AI

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“…Collision avoidance systems have the technology to navigate within the COL-REGs (Ning et al 2020;Shaobo et al 2020). However, as the COLREGs are written for manned vessels, some of the current rules present problems (Porathe 2019;Pedersen et al 2020).…”

Section: Colregs and Massmentioning

confidence: 99%

Autonomous ships and the collision avoidance regulations: a licensed deck officer survey

Hannaford

Maes

Hassel

2022

WMU J Marit Affairs

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International interest in Maritime Autonomous Surface Ships (MASS) is on the rise. This exploratory research presents insights of a sample of licensed deck officers (LDOs) regarding the potential future of the Collision Avoidance Regulations (COLREGs) with the implementation of MASS. At present, there is much discussion in the maritime industry on if and how the COLREGs will need to be amended to be able to be applied to MASS. Limited research is published from the key perspective of the LDO. Qualitative and quantitative methods are used, including a literature review and a multiple-choice survey. Data is analyzed via descriptive statistics, and commonalities within the results are investigated as well as years of experience with practicing the COLREGs. Results show that many barriers exist when applying the COLREGs to MASS, and minor amendments to certain terms and definitions are recommended. Moreover, the COLREGs should not be quantified, and MASS should be identifiable from other vessels. LDOs with more experience with practicing the COLREGs are found to be slightly more open to changing the rules versus LDOs with less experience. When compared to the results of the International Maritime Organization’s regulatory scoping exercise, the results of this study are found to be in congruence. This research provides valuable insights for the ongoing discussion of the future of MASS operation in the maritime industry.

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“…Shengke [17] use genetic algorithms to optimize paths that avoid collisions at open sea. Jun [18] proposed a modified fuzzy dynamic risk of collision model based on time and space collision risk index to generate paths and used multi objective genetic algorithm to optimize paths based on time, economy, COLREGs, and safety. Compared to the above approaches, VORRT-COLREGs provides fast, safe, near-optimal, physically realizable paths for ASVs.…”

Section: Related Workmentioning

confidence: 99%

VORRT-COLREGs: A Hybrid Velocity Obstacles and RRT Based COLREGs-Compliant Path Planner for Autonomous Surface Vessels

Dubey¹,

Louis²

2021

Preprint

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This paper presents VORRT-COLREGs, a hybrid technique that combines velocity obstacles (VO) and rapidlyexploring random trees (RRT) to generate safe trajectories for autonomous surface vessels (ASVs) while following nautical rules of the road. RRT generates a set of way points and the velocity obstacles method ensures safe travel between way points. We also ensure that the actions of ASVs do not violate maritime collision guidelines. Earlier work has used RRT and VO separately to generate paths for ASVs. However, RRT does not handle highly dynamic situations well and and VO seems most suitable as a local path planner. Combining both approaches, VORRT-COLREGs is a global path planner that uses a joint forward simulation to ensure that generated paths remain valid and collision free as the situation changes. Experiments were conducted in different types of collision scenarios and with different numbers of ASVs. Results show that VORRT-COLREGs generated collision regulations (COLREGs) complaint paths in open ocean scenarios. Furthermore, VORRT-COLREGs successfully generated compliant paths within traffic separation schemes. These results show the applicability of our technique for generating paths for ASVs in different collision scenarios. To the best of our knowledge, this is the first work that combines velocity obstacles and RRT to produce safe and COLREGs complaint path for ASVs.

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COLREGs-Compliant Unmanned Surface Vehicles Collision Avoidance Based on Multi-Objective Genetic Algorithm

Cited by 40 publications

References 43 publications

Autonomous Collision Avoidance at Sea: A Survey

Autonomous Collision Avoidance at Sea: A Survey

Autonomous ships and the collision avoidance regulations: a licensed deck officer survey

VORRT-COLREGs: A Hybrid Velocity Obstacles and RRT Based COLREGs-Compliant Path Planner for Autonomous Surface Vessels

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