Wireless sensor networks accommodating the mobility of nodes will play important roles in the future. In residential, rehabilitation, and clinical settings, sensor nodes can be attached to the body of a patient for long-term and uninterrupted monitoring of vital biomedical signals. Likewise, in industrial settings, workers as well as mobile robots can carry sensor nodes to augment their perception and to seamlessly interact with their environments. Nevertheless, such applications require reliable communications as well as high throughput. Considering the primary design goals of the sensing platforms (low-power, affordable cost, large-scale deployment, longevity, operating in the ISM band), maintaining reliable links is a formidable challenge. This challenge can partially be alleviated if the nature of link quality fluctuation can be known or estimated on time. Indeed, higher-level protocols such as handover and routing protocols rely on knowledge of link quality fluctuation to seamlessly transfer communication to alternative routes when the quality of existing routes deteriorates. In this article, we present the result of extensive experimental study to characterise link quality fluctuation in mobile environments. The study focuses on slow movements (<5 km h-1) signifying the movement of people and robots and transceivers complying to the IEEE 802.15.4 specification. Hence, we deployed mobile robots that interact with strategically placed stationary relay nodes. Our study considered different types of link quality characterisation metrics that provide complementary and useful insights. To demonstrate the usefulness of our experiments and observations, we implemented a link quality estimation technique using a Kalman Filter. To set up the model, we employed two link quality metrics along with the statistics we established during our experiments. The article will compare the performance of four proposed approaches with ours.