Efficient robot-sensor network distributed SEIF range-only SLAM

This paper is motivated by schemes of robot-sensor network cooperation where sensor nodes (beacons) are used as landmarks for Range-Only (RO) Simultaneous Localization and Mapping (SLAM). Most existing RO-SLAM techniques consider beacons as passive devices disregarding the sensing, computing and communication capabilities they are actually endowed with. This paper proposes a Range-Only scheme based on Sparse Extended Information Filters (SEIF) that efficiently exploits their capabilities. The robot computes the SLAM prediction stage and distributes the update stage among beacons within its sensing area. The proposed scheme naturally integrates robot-beacon and inter-beacon measurements, significantly improving map and also robot estimations. Our scheme inherits from SEIF its efficiency and scalability and further reduces robot computational burden by exploiting the beacons computing capability. As a result, it has lower error and lower computer requirements than traditional methods. This paper presents the scheme, evaluates and compares its performance in simulations and real experiments.