Global path planning and multi-objective path control for unmanned surface vehicle based on modified particle swarm optimization (PSO) algorithm

Guo, Xinghai; Ji, Mingjun; Zhao, Ziwei; Wen, Dusu; Weidan, Zhang

doi:10.1016/j.oceaneng.2020.107693

Cited by 99 publications

(56 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to ensure that the mobile robot does not collide with the edge of the obstacle during the movement and ensure the smooth progress of each turn, the size of the obstacle is properly expanded in this paper, and then a certain safe distance is reserved. e safe distance is the radius of the mobile robot, and the robot can be simplified as a particle to deal with [19]. e grid number is used to represent the specific positions of robots and obstacles, in which the white grid is the free grid, representing the passable area, while the black grid is the obstacle area, which is impassable for mobile robots.…”

Section: Environmentalmentioning

confidence: 99%

Smooth Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm

Wang

Zhao

et al. 2021

Journal of Robotics

View full text Add to dashboard Cite

Aiming at the problems of slow convergence, easy to fall into local optimum, and poor smoothness of traditional ant colony algorithm in mobile robot path planning, an improved ant colony algorithm based on path smoothing factor was proposed. Firstly, the environment map was constructed based on the grid method, and each grid was marked to make the ant colony move from the initial grid to the target grid for path search. Then, the heuristic information is improved by referring to the direction information of the starting point and the end point and combining with the turning angle. By improving the heuristic information, the direction of the search is increased and the turning angle of the robot is reduced. Finally, the pheromone updating rules were improved, the smoothness of the two-dimensional path was considered, the turning times of the robot were reduced, and a new path evaluation function was introduced to enhance the pheromone differentiation of the effective path. At the same time, the Max-Min Ant System (MMAS) algorithm was used to limit the pheromone concentration to avoid being trapped in the local optimum path. The simulation results show that the improved ant colony algorithm can search the optimal path length and plan a smoother and safer path with fast convergence speed, which effectively solves the global path planning problem of mobile robot.

show abstract

Section: Environmentalmentioning

confidence: 99%

Smooth Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm

Wang

Zhao

et al. 2021

Journal of Robotics

View full text Add to dashboard Cite

show abstract

“…Distribution is an important part of the cooperative alliance game. This paper uses the Shapley value method for distribution [19]. The Shapley value of the participant is as follows, where i is the participant:…”

Section: The Basic Concept Of Cooperative Gamesmentioning

confidence: 99%

“…In the formula (19), Due to the high internal voltage levels of the distribution network operators, the complex network structure, the many types of equipment and the poor operating safety environment, the economic optimization of the distribution network needs to meet the power flow constraints and safety constraints. The mathematical model is as follows:…”

Section: Establishment and Solution Of Cooperative Game Modelmentioning

confidence: 99%

Coordination and Optimization of CCHP Microgrid Group Game Based on the Interaction of Electric and Thermal Energy Considering Conditional Value at Risk

Liu

Shusen

2021

IEEE Access

View full text Add to dashboard Cite

With the continuous advancement of power market reform, a cluster system composed of multiple microgrids can effectively improve the mutual support of energy between microgrids and improve the stability of system operation. This article comprehensively considers cogeneration, heat pumps, electrical energy storage, and thermal energy storage equipment to establish a framework for a multi-microgrid system. Secondly, due to the heterogeneity of wind power output, load demand and equipment parameters of different microgrids, considering the possibility of collaboration among multiple microgrids, the essence of energy complementarity to increase overall revenue is explained. On this basis, a cooperative game optimization dispatching model for microgrid group of cooling and heating power sources considering energy interaction is proposed. The Shapley value distribution method is used to distribute the surplus value generated by the cooperation. Furthermore, considering the uncertainty of wind power and load in multi-micro grids, a stochastic programming model based on conditional value-at-risk is established. The simulation analysis shows that the model proposed in this paper can effectively improve the surplus power and heat absorption capacity of the microgrid cooperative alliance, while reducing the impact on the power interaction of the main grid. The value of the conditional risk considered is also multi-microgrid. The system provides a reference plan for the trade-off between economic benefits and risk levels.

show abstract

“…As for the optimization algorithm selection, particle swarm optimization (PSO) has been widely used in the multiobjective optimization (MOO) field [24] [25]. It is a global search algorithm first proposed by Eberhart and Kenedy in 1995 [26].…”

Section: A Backgroundmentioning

confidence: 99%

“…Inertia weight w refers to the ability of a particle to maintain the previous state of motion. At present, the setting methods of inertia weight mainly include constant setting, linear adjustment, fuzzy adaptive, and random adjustment [24] [25]. Shi et al suggested setting the inertia weight to 0.8 [47].…”

Section: ) Particle Swarm Optimization Parameter Settingsmentioning

confidence: 99%