Multiple obstacle avoidance

Motion Attribute-based Clustering and Collision Avoidance of Multiple In-water Obstacles by Autonomous Surface Vehicle

Our work proposes a novel real-time non-myopic obstacle avoidance method, 
allowing an ASV that has only partial knowledge of the surroundings
within the sensor radius to navigate in high-traffic maritime scenarios. 
By using
(1) a clustering method based on motion attributes of other obstacles; 
(2) a geometric framework for identifying the feasible action space; and 
(3) a multi-objective optimization to determine the best action
Collision avoidance behavior for controlled ASV, using state-of-the art (left) vs. proposed method (right) under congested traffic with multiple obstacles

Here is a video I have presented at IROS2022.