Autonomous mobile robots (AMRs) interacting with an a priori distributed wireless sensor network (WSN)
in a region can address the three-tier challenge of navigating in unknown environments: (i) identifying
target locations, (ii) planning paths to the targets, and (iii) efficiently executing the navigation paths
to the targets. This paper presents low-complexity algorithms to address the second-tier and third-tier
challenges, i.e., efficiently planning and executing paths to target locations. These novel approaches use
only the information inherent in WSNs, i.e., received signal strength (RSS). The objective is to have the
AMR navigate to a target location by: (i) producing an RSS-based artificial magnitude distribution in the
navigation region, (ii) using particle filtering based bearing estimation for orientation information, and
(iii) using interpolated pseudogradient for efficient path planning and navigation. Here, the AMR does not
require: (i) the global location information for itself or the WSN, (ii) a priori information of the direction of
a target location, or (iii) sophisticated ranging equipment for prior mapping. The AMR relies only on local,
neighborhood information and low-cost wireless directional antennas for navigation. Real-world and
simulation experiments, using a variety of node-densities, demonstrate the effectiveness of the proposed
schemes. The low-cost, low-complexity advantages of the WSN–AMR interactive navigation provide for
efficient map-less and ranging-less navigation methods.