Toward Autonomous Target Navigation in Indoor Environments via Wireless Sensing

This work addresses the problem of autonomous target navigation in indoor environments through wireless sensing. To accomplish accurate navigation, it proposes a novel yet simple localization algorithm based on basic geometry and Weighted Central Mass (WCM) by extracting range measurements from received wireless signals. To avoid obstacle collision in the considered indoor environments, the work proposes a new obstacle detection scheme that is based on wireless sensing, where abrupt signal fluctuations throughout the target's movement are exploited to detect and avoid obstructions. Therefore, integrating the two proposed solutions allows for partially autonomous target navigation in indoor environments without resorting to expensive and complex hardware, such as LiDARs or cameras. The proposed solutions are validated through both simulation and experimental test beds, that corroborate their effectiveness, both in terms of navigation and obstacle detection accuracy.