Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  consider the problem of robot tracking and navigation toward a moving goal. The goal's maneuvers are not a priori known to the robot. Thus, off-line strategies are not effective. To model the robot and the goal,  use geometric rules combined with kinematics equations expressed in a polar representation. The intent of the strategy is to keep the robot beten a reference point, called the observer, and the goal.  prove under certain assumptions that the robot navigating using this strategy reaches the moving goal successfully. In the presence of obstacles, the method is combined with an obstacle avoidance algorithm. The robot then moves in two modes, the navigation mode and the obstacle avoidance mode. Simulation of various scenarios highlights the efficiency of the method and provides an instructive comparison beten the paths obtained for different reference points.
['Fethi Belkhouche', 'Boumediene Belkhouche', 'P. Rastgoufard']
I am writing a research paper on a idea Line of sight robot navigation toward a moving goal
[{"from": "human", "value": "I am writing a research paper on a idea Line of sight robot navigation toward a moving goal"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  consider the problem of robot tracking and navigation toward a moving goal. The goal's maneuvers are not a priori known to the robot. Thus, off-line strategies are not effective. To model the robot and the goal,  use geometric rules combined with kinematics equations expressed in a polar representation. The intent of the strategy is to keep the robot beten a reference point, called the observer, and the goal.  prove under certain assumptions that the robot navigating using this strategy reaches the moving goal successfully. In the presence of obstacles, the method is combined with an obstacle avoidance algorithm. The robot then moves in two modes, the navigation mode and the obstacle avoidance mode. Simulation of various scenarios highlights the efficiency of the method and provides an instructive comparison beten the paths obtained for different reference points."}]