Adaptive sensor management for UGV monitoring based on risk maps

Abstract

Because of the recent advances in sensor technology, unmanned ground vehicles (UGVs) are equipped with various high-performance sensors to improve their mission performance. The energy consumption of the sensors is a critical issue because most UGVs operate on rechargeable batteries while conducting their missions. In particular, efficient sensing has become a crucial challenge due to the growing demand for advanced intelligent monitoring missions. However, while previous studies have focused on power consumption models for vehicle locomotion, they have not fully addressed the high energy consumption of sensors. This study proposes an adaptive sensor-management algorithm to address the critical issue of energy consumption by considering the monitoring and navigation sensors that are widely used in UGV monitoring. After characterizing the proposed adaptive sensor-management strategy based on a risk map composed of monitoring and saving zones, we present a power consumption model to quantify the energy savings of the sensors. Furthermore, the optimal interval was derived to minimize power consumption during UGV monitoring. The proposed algorithm can minimize the energy consumption by adjusting the optimal interval according to the mission environment. We demonstrate the results of our analysis through various evaluations.