Autonomous navigation using received signal strength and bearing-only pseudogradient interpolation

Autonomousmobile robots (AMRs) interactingwith an a prioridistributedwireless 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 theWSN, (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. © 2015 Elsevier B.V. All rights reserved. ✩ The researchwas carried out at the Center for Robotics and IntelligentMachines (CRIM) in the Department of Electrical and Computer Engineering at North Carolina State University, in Raleigh, NC. ∗ Correspondence to: Department of Advanced Robotics, Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genova, Italy. Tel.: +39 010 71781 805. E-mail addresses: [email protected], [email protected] (N. Deshpande), [email protected] (E. Grant), [email protected] (T.C. Henderson), [email protected], [email protected] (M.T. Draelos). 1 Present Address: Department of Biomedical Engineering, Duke University, Durham, NC, 27708, USA. http://dx.doi.org/10.1016/j.robot.2015.10.009 0921-8890/© 2015 Elsevier B.V. All rights reserved.