Event-Triggered Asynchronous Fusion Localization for an Autonomous Mobile Robot With a Camera and UWB in Confined Indoor Spaces

Accurate indoor localization for autonomous mobile robots remains challenging in confined indoor spaces using a camera and an ultra-wideband (UWB) due to asynchronous sampling, heavy-tailed noises and missing measurements. In this article, event-triggered asynchronous fusion localization is investigated for an autonomous mobile robot using a camera and an UWB in confined indoor spaces. A dynamic event-triggered mechanism is proposed to save communication resource by reducing measurement transmission. A compensation strategy is designed to recover non-triggered measurements for local estimation. An UWB local estimator is designed addressing heavy-tailed noises and uncertainties by measurement compensation. A visual local estimator is designed under missing measurement compensation using fusion estimate feedback. A distributed fusion estimator is proposed to achieve fusion estimates by a matrix-weighted fusion method. Effectiveness of the proposed event-triggered asynchronous fusion localization is demonstrated through experimental results in an indoor narrow corridor.