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The planning of safe paths is an important issue for autonomous robot systems. The Probabilistic Foam method (PFM) is a planner that guarantees safe paths bounded by a sequence of structures called bubbles that provides safe regions. This method performs the planning by covering the free configuration space with bubbles, an approach analogous to a breadth-first search. To improve the propagation process and keep the safety, we present three algorithms based on Probabilistic Foam: Goal-biased Probabilistic Foam (GBPF), Radius-biased Probabilistic Foam (RBPF), and Heuristic-guided Probabilistic Foam (HPF); the last two are proposed in this work. The variant GBPF is fast, HPF finds short paths, and RBPF finds high-clearance paths. Some simulations were performed using four different maps to analyze the behavior and performance of the methods. Besides, the safety was analyzed considering the new propagation strategies.

This paper presents a communication network for a squadron of unmanned aerial vehicles (UAVs) to be used in the scanning rocket impact area for Barreira do Inferno Launch Center—CLBI (Rio Grande do Norte, Brazil), aiming at detecting intruder boats. The main features of communication networks associated with multi-UAV systems are presented. This system sends information through Wireless Sensor Networks (WSN). After comparing and analyzing area scanning strategies, it presents the specification of a data communication network architecture for a squadron of UAVs within a sensor network using XBee Pro 900HP S3B modules. A brief description is made about the initial information from the construction of the system. The embedded hardware and the design procedure of a dedicated communication antenna to the XBee modules are presented. In order to evaluate the performance of the proposed architecture in terms of robustness and reliability, a set of experimental tests in different communication scenarios is carried out. Network management software is employed to measure the throughput, packet loss and other performance indicators in the communication links between the different network nodes. Experimental results allow verifying the quality and performance of the network nodes, as well as the reliability of the communication links, assessing signal received quality, range and latency.