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We propose and implement a hybrid navigational strategy for mobile robots for data collection tasks in sparsely deployed sensor networks. Our approach presents an alternative to the routing algorithms used in wireless sensor networks which focus on the minimization of energy consumption of each node which is mainly due to data transmission. The method has two layers: i) Reactive Layer in which the data collected from a sensor node is modelled as a potential function whose gradient attracts the robot and ii) Planning Layer, that dictates the action the robot must take to collect sensor data. Results from both simulation and real world experiments showing the performance of the proposed methodology are shown, compared and discussed.