ActionSLAM on a smartphone: At-home tracking with a fully wearable system

We present SmartActionSLAM, an Android smartphone application that performs location tracking in home and office environments. It uses the integrated motion sensors of the smartphone and an optional foot-mounted inertial measurement unit to track a person. The application implements an instance of the ActionSLAM algorithmic framework. ActionSLAM combines pedestrian dead reckoning with the observation of activities (in SmartActionSLAM: sitting and standing still) to build and update a local landmark map of the user's environment. This map is used to compensate for error accumulation of dead reckoning in a particle filter framework. We show that it is possible to execute the ActionSLAM algorithm in real-time on a smartphone without platform-specific optimizations. Furthermore, we analyze the localization performance of the application in six constrained and two real-life recordings. When using only the smartphone's internal sensors, tracking was adequate in most constrained setups, but failed in the real-world scenarios because of errors in recognizing irregular leg movements. By including the foot-mounted sensor, mapping with a mean landmark positioning error of <; 0.5m and robustness > 90% was achieved in all environments. Smart-ActionSLAM is fully wearable and requires no infrastructure in the environment. The approach is therefore ideally suited for rapid deployment in home and office environments, as for example required in patient monitoring studies.