Exploiting Heterogeneity in Teams of Robotic Agents Using Hybrid Communications Heterogeneous teams of robotic agents using hybrid optical wireless and radio frequency intermittent network communications and cloud based computing resources can achieve complex missions efficiently through improved mission and motion planning. Although radio frequency communications dominate the robotic network field, they are limited in range due to spectrum congestion and subject to interference from noise or hostile jamming. Optical communication has many advantages such as higher bandwidth and focused beam, however the lineofsight requirement generally limits its range and application. Maintaining a continuously connected network graph between agents is also often overly restrictive, dramatically limiting their freedom of motion and therefore efficiency. In this paper we present a method to coordinate a heterogeneous team of agents using an intermittent optical and radio communication network which improves the execution of the mission considering the abilities and resources of the various agents. Realistic simulation and experimental results demonstrate the effectiveness of this new approach.

Fast and Parallel Wireless Communication Backbone Deployment with Networked Robots Disaster robotics have gained considerable attention in the last decade while providing support for the emergency teams in search and rescue operations. Here, we propose a system to support first responders, such as firefighters and police officers, by establishing a communication network connecting multiple clients. The clients are the access points for the rescue teams. The objective is to deploy robots equipped with communication devices in such a manner that the clients are able to communicate among themselves. We focus on minimizing the deployment time. Our approach allows to combine links when computing the backbone. Then, our proposed method decomposes the problem into a set of local communication networks that when solved connects all clients in a network. Unlike previous works, the deployment is done in parallel, which decreases the time to set up the network. Our method uses realistic communication metrics to determine the connectivity between devices and to deploy the robots in the environment. We show using both simulations and physical experiments the feasibility of our solution.