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In this article, a robot system for intelligent water surface cleaner named IWSCR is developed to collect floating plastic garbage. It is able to accomplish three major tasks autonomously, i.e., cruise and detection, tracking and steering, and grasping and collection. The challenges behind these tasks involve how to realize the accurate and real-time garbage detection, how to resist the disturbances while IWSCR conducts vision-based steering, and how to grasp the floating garbage reliably despite the turbulent conditions on the surface of the water. To overcome these difficulties, three key techniques are proposed for IWSCR. First, the YOLOv3 network, which is widely applied in the high speed and accuracy object detection field, is trained on the proposed floating garbage dataset to realize accurate and real-time garbage detection. Next, to improve the ability of resisting disturbances, a control law based on the sliding-mode controller is proposed for vision-based steering. Furthermore, inspired by the stability of floating bottles in fluid, a feasible grasping strategy is utilized for IWSCR. Finally, the experimental results demonstrate that IWSCR is competent to carry out the task of water surface cleaning.
Kong et al. (Thu,) studied this question.