This academic article delves into state estimation in multi-sensor fusion navigation. It discusses the importance of navigation for intelligent robots and the role of multi-sensor fusion in providing precise position and orientation. The paper compares two methods of state estimation: optimization and filtering. It argues that while optimization-based frameworks have shown better performance in terms of accuracy, both methods should be theoretically equivalent. The authors suggest that differences in real-time operation strategies may cause this discrepancy. The paper concludes by suggesting future research should focus on improving algorithms and strategies, rather than state estimation approaches.
Publication date: 12 Jan 2024
Project Page: Not specified
Paper: https://arxiv.org/pdf/2401.05836
