A general Gaussian-mixture approach for range-only mapping using multiple hypotheses

Radio signal-based localization and mapping is becoming more interesting as applications involving the collaboration between robots and static wireless devices are more common. Under certain assumptions, the problem is basically equivalent to the range-only localization and mapping problem. The paper presents a method for mapping with a mobile robot the position of a set of nodes using radio signal measurements. It uses Gaussian Mixtures for undelayed initialization of the position of the wireless nodes. The paper shows how the approach can be integrated within a Kalman Filter. This way, information can be used in the filter since the first measurement. The paper describes simulations to verify the feasibility of the approach, and presents results obtained with experimental data involving one mobile robot and a wireless sensor network.