Intermittently Connected Robotic Networks in Dynamic Environments

Autonomous technologies are most urgently needed in unreachable or unsafe situations for human-beings, or with monotonous and repetitive tasks. A wide variety of these situations or tasks occur in dynamic environments and require solutions in a long-term and persistent fashion. With the increasing complexity of tasks, the deployment of multiple robots in the same task space not only boosts the efficiency, but also introduces new capabilities of the robotic systems through cooperation, coordination, and collaboration across individuals. In a multi-robot team, each robot individually interacts with the environment and jointly synthesizes a system delivering desired solutions collectively. The connections between these robots, e.g. the capability of exchanging materials or information, are essential to maintaining a robust, resilient, and secure team while handling challenges or adversary together. However, establishing and/or maintaining such a persistently connected robotics network evidently limits the coverage of the whole team, or often is not even feasible. This work focuses on the approach of leveraging the dynamics of the environment to realize smart motion planning so that each robot can travel around the task space, and establish temporal connections with robots relatively far away. The reoccurring temporal connections created through this method can collectively form an intermittently connected network over time, providing guaranteed and resilient performance.