This paper presents a new algorithm for a real-time obstacle avoidance for autonomous surface vehicles (ASV) that is capable of undertaking preemptive actions in complex and challenging scenarios. The algorithm is called adaptive velocity obstacle avoidance (AVOA) and takes into consideration the kinematic and dynamic constraints of autonomous vessels along with a protective zone concept to determine the safe crossing distance to obstacles. A configuration space that includes both the position and velocity of static or dynamic elements within the field-of-view of the ASV is supporting a particle swarm optimization procedure that minimizes the risk of harm and the deviation towards a predefined course while generating a navigation path with capabilities to prevent potential collisions. Extensive experiments demonstrate the ability of AVOA to select a velocity estimative for ASVs that originates a smoother, safer and, at least, two times more effective collision-free path when compared to existing techniques.

While autonomous underwater vehicles (AUVs) are increasingly being used to perform mine countermeasures (MCM) operations, the capability of these systems is limited by the efficiency of the planning process. In this paper we study the problem of multiobjective MCM mission planning with an AUV. In order to overcome the inherent complexity of the problem, a multi-stage algorithm is proposed and evaluated. Our algorithm combines an evolutionary algorithm (EA) with a local search procedure based on simulated annealing (SA), aiming at a more flexible and effective exploration and exploitation of the search space. An artificial neural network (ANN) model was also integrated in the evolutionary procedure to guide the search. The results show that the proposed strategy can efficiently identify a higher quality solution set and solve the mission planning problem.

In this article, we describe the analysis, design and implementation of a control architecture for a mobile platform to autonomously carry out transportation, surveillance and inspection tasks in semi-structured industrial environments. Based on a hierarchical structure composed by the organization, coordination and functional levels organized linguistically and structured according to the principle of increasing precision with decreasing intelligence, this control architecture permits the real-time parallel execution of tasks.