Motion Plan of Maritime Autonomous Surface Ships by Dynamic Programming for Collision Avoidance and Speed Optimization
Maritime Autonomous Surface Ships (MASS) with advanced guidance, navigation, and control capabilities have attracted great attention in recent years. Sailing safely and efficiently are critical requirements for autonomous control of MASS. The MASS utilizes the information collected by the radar, cam...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-01-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/2/434 |
| _version_ | 1828352967826210816 |
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| author | Xiongfei Geng Yongcai Wang Ping Wang Baochen Zhang |
| author_facet | Xiongfei Geng Yongcai Wang Ping Wang Baochen Zhang |
| author_sort | Xiongfei Geng |
| collection | DOAJ |
| description | Maritime Autonomous Surface Ships (MASS) with advanced guidance, navigation, and control capabilities have attracted great attention in recent years. Sailing safely and efficiently are critical requirements for autonomous control of MASS. The MASS utilizes the information collected by the radar, camera, and Autonomous Identification System (AIS) with which it is equipped. This paper investigates the problem of optimal motion planning for MASS, so it can accomplish its sailing task early and safely when it sails together with other conventional ships. We develop velocity obstacle models for both dynamic and static obstacles to represent the potential conflict-free region with other objects. A greedy interval-based motion-planning algorithm is proposed based on the Velocity Obstacle (VO) model, and we show that the greedy approach may fail to avoid collisions in the successive intervals. A way-blocking metric is proposed to evaluate the risk of collision to improve the greedy algorithm. Then, by assuming constant velocities of the surrounding ships, a novel Dynamic Programming (DP) method is proposed to generate the optimal multiple interval motion plan for MASS. These proposed algorithms are verified by extensive simulations, which show that the DP algorithm provides the lowest collision rate overall and better sailing efficiency than the greedy approaches. |
| first_indexed | 2024-04-14T02:01:06Z |
| format | Article |
| id | doaj.art-2334c8609b5f4980990cfeef408767da |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T02:01:06Z |
| publishDate | 2019-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2334c8609b5f4980990cfeef408767da2022-12-22T02:18:49ZengMDPI AGSensors1424-82202019-01-0119243410.3390/s19020434s19020434Motion Plan of Maritime Autonomous Surface Ships by Dynamic Programming for Collision Avoidance and Speed OptimizationXiongfei Geng0Yongcai Wang1Ping Wang2Baochen Zhang3School of Software and Microelectronics, Peking University, Beijing 100871, ChinaDepartment of Computer Sciences, Renmin University of China, Beijing 100872, ChinaSchool of Software and Microelectronics, Peking University, Beijing 100871, ChinaChina Waterborne Transport Research Institute, Beijing 100088, ChinaMaritime Autonomous Surface Ships (MASS) with advanced guidance, navigation, and control capabilities have attracted great attention in recent years. Sailing safely and efficiently are critical requirements for autonomous control of MASS. The MASS utilizes the information collected by the radar, camera, and Autonomous Identification System (AIS) with which it is equipped. This paper investigates the problem of optimal motion planning for MASS, so it can accomplish its sailing task early and safely when it sails together with other conventional ships. We develop velocity obstacle models for both dynamic and static obstacles to represent the potential conflict-free region with other objects. A greedy interval-based motion-planning algorithm is proposed based on the Velocity Obstacle (VO) model, and we show that the greedy approach may fail to avoid collisions in the successive intervals. A way-blocking metric is proposed to evaluate the risk of collision to improve the greedy algorithm. Then, by assuming constant velocities of the surrounding ships, a novel Dynamic Programming (DP) method is proposed to generate the optimal multiple interval motion plan for MASS. These proposed algorithms are verified by extensive simulations, which show that the DP algorithm provides the lowest collision rate overall and better sailing efficiency than the greedy approaches.https://www.mdpi.com/1424-8220/19/2/434motion planspeed optimizationunmanned surface vehiclevelocity obstacleconventional shipsdynamic programmingmaritime autonomous surface ships |
| spellingShingle | Xiongfei Geng Yongcai Wang Ping Wang Baochen Zhang Motion Plan of Maritime Autonomous Surface Ships by Dynamic Programming for Collision Avoidance and Speed Optimization Sensors motion plan speed optimization unmanned surface vehicle velocity obstacle conventional ships dynamic programming maritime autonomous surface ships |
| title | Motion Plan of Maritime Autonomous Surface Ships by Dynamic Programming for Collision Avoidance and Speed Optimization |
| title_full | Motion Plan of Maritime Autonomous Surface Ships by Dynamic Programming for Collision Avoidance and Speed Optimization |
| title_fullStr | Motion Plan of Maritime Autonomous Surface Ships by Dynamic Programming for Collision Avoidance and Speed Optimization |
| title_full_unstemmed | Motion Plan of Maritime Autonomous Surface Ships by Dynamic Programming for Collision Avoidance and Speed Optimization |
| title_short | Motion Plan of Maritime Autonomous Surface Ships by Dynamic Programming for Collision Avoidance and Speed Optimization |
| title_sort | motion plan of maritime autonomous surface ships by dynamic programming for collision avoidance and speed optimization |
| topic | motion plan speed optimization unmanned surface vehicle velocity obstacle conventional ships dynamic programming maritime autonomous surface ships |
| url | https://www.mdpi.com/1424-8220/19/2/434 |
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