Towards use of Dijkstra Algorithm for Optimal Navigation of an Unmanned Surface Vehicle in a Real-Time Marine Environment with results from Artificial Potential Field

AutoTuning Environment for Static Obstacle Avoidance Methods Applied to USVs

“…Therefore, these methods do not ensure that the vehicle reaches the target if there are local minima. For this reason, in order to provide a complete solution to the problem of autonomous navigation [1][2][3], it is necessary to combine obstacle avoidance methods or reactive methods [8,10,[12][13][14][15][21][22][23][24][25][26][27][28][29][30][31] with global or path planning algorithms [3,7,17,19,20]. In this sense, the obstacle scenarios studied in this work are focused only on the reactive part, unknown scenarios that the autonomous vehicle discovers while navigating.…”

“…Thus, B osb is generated from the measurements delivered by the LIDAR sensor model, considering each beam from the Model (10) as an obstacle, see Equation (24). Furthermore, with the purpose that the algorithm considers the direction of the velocity vector, in the Equations (18), (19) and (22), ψ(k) is replaced by χ(k). One of the executions of the LROABRA algorithm implemented in this work is shown in Figure 8.…”

“…where seg It is important to highlight that we have chosen to model each obstacle as a rectangle due to the facility for generating scenarios from these polygons. However, this LIDAR sensor model can also be used in the presence of irregular polygons such as the ones that define the marine environments [16,17,19]. For this purpose, two approaches can be taken.…”

“…Once the state of the vehicle is known, the detection system processes the information received by the surrounding sensors in order to generate a model of the environment in which the USV is located [6][7][8][9][10]. Using this model of the environment, the guidance system (composed by algorithms of: obstacle avoidance [8,[11][12][13][14][15][16], path following [4,5,17,18] and path planning [3,7,17,19,20]) demands the course and speed setpoints which guide the vessel safely to its goal. With the aim of ensuring that the vehicle reaches these setpoints, the control system commands the vessel's actuators (propulsion system and steering machine) [4,5].…”

Modified A* Algorithm for Obstacle Avoidance for Unmanned Surface Vehicle

“…An effective path planning approach is required to improve the level of autonomy of USVs. When calculating the most efficient path between a starting point and a goal point in a grid map consisting of nodes, Dijkstra's algorithm is often used (Singh et al, 2018;Niu et al, 2016a). The more general algorithm, A*, which is the best-first search algorithm, is also used for path planning.…”