Contributions to Integrity and Collaboration in Dynamic Sensor Networks

Abstract

Reliable and safe navigation of autonomous systems is an active field of research, particularly in the context of complex urban environments. A key challenge is navigation integrity, defined as the trust in the correctness of the estimated system state; the transfer of this concept from aviation to collaborative multi-agent systems remains an open research challenge. Addressing this gap, this paper presents the methodological developments and key findings of the DFG-funded i.c.sens research project, which focused on navigation integrity in dynamic collaborative sensor networks. To account for key influencing factors and to structure the research activities accordingly, three central research directions are defined: Observations (sensor characteristics and uncertainties), Methodology (state estimation and integrity monitoring), and Map (dynamic, uncertainty-aware environmental representations). To evaluate the developed approaches and assess their performance under realistic conditions, extensive experiments were conducted. Based on experimental results obtained from publicly available datasets as well as datasets collected by the i.c.sens group, the paper summarizes key achievements of i.c.sens in integrity-aware state estimation under realistic urban conditions. These results show improved navigation performance through multi-agent information exchange, through rigorous uncertainty modeling and through the conception and usage of sophisticated map concepts. Based on these findings, we highlight remaining integrity challenges in dynamic sensor networks and point out promising directions for future research.