Target Localization and Autonomous Navigation Using Wireless Sensor Networks—A Pseudogradient Algorithm Approach

Abstract

Autonomous mobile robots (AMRs) operating in unknown environments face twin challenges: 1) localization and 2) efficient directed navigation. This paper describes a two-tiered approach to solving these challenges: 1) by developing novel wireless-sensor-network (WSN)-based localization methods and 2) by using WSN-AMR interaction for navigation. The goal is to have an AMR travel from any point within a WSN-covered region to an identified target location without the aid of global sensing and position information. In this research, the target is reached as follows: 1) by producing a magnitude distribution within the WSN region that has a target-directed pseudogradient (PG) and 2) by having the WSN efficiently navigate the AMRs using the PG. This approach utilizes only the topology of the network and the received signal strength (RSS) among the sensor nodes to create the PG. This research shows that, even in the absence of global positioning information, AMRs can successfully navigate toward a target location using only the RSS in their local neighborhood to compute an optimal path. The utility of the proposed scheme is proved through extensive simulation and hardware experiments.