An Integrated Sparsity and Model-Based Probabilistic Framework for Estimating the Spatial Variations of Communication Channels
In the past few years, the sensor network revolution has created the possibility of exploring and controlling the environment in ways not possible before. The vision of a multi-agent robotic network cooperatively learning and adapting in harsh unknown environments to achieve a common goal is closer than ever. A mobile cooperative network needs to maintain its connectivity in order to accomplish its task. In order to achieve this, each robot should consider the impact of its motion decisions on its link qualities, when planning its trajectory. This requires each robot to assess the quality of the communication links in the locations that it has not yet visited.