Optimization of Multi-Attribute Tasks for Underwater Motion of Robotic Sensor Agents

Target detection, identification, and tracking are tasks of great importance in counterterrorism preparations. The development of a new generation of mobile autonomous wireless robotic sensor agents provides new advanced opportunities for target monitoring and tracking. We are particularly interested in the investigation of the underwater motion of the mobile robotic sensor agents. However, the trajectory of the underwater motion of a robotic sensor agent from the initial point to the destination significantly differs from the ground motion trajectory. Firstly, an underwater vehicle is affected by the current flow and its motion strongly depends on the structure of the river (cross-section shape, bottom type, etc) or ocean. Secondly, the battery power is limited and it almost impossible to recharge the batteries while the agent is underwater. Also, the time for robotic sensor agents to reach the target may be crucial. Consequently, finding the fastest path to the destination given a water stream is important. Thus, how should cluster of underwater robotic sensors move to optimize multi-attribute tasks?