Luppi Isabella, Bhatt Neel Pratik, Hashemi Ehsan
Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada.
Sensors (Basel). 2024 May 4;24(9):2927. doi: 10.3390/s24092927.
A distributed state observer is designed for state estimation and tracking of mobile robots amidst dynamic environments and occlusions within distributed LiDAR sensor networks. The proposed novel framework enhances three-dimensional bounding box detection and tracking utilizing a consensus-based information filter and a region of interest for state estimation of mobile robots. The framework enables the identification of the input to the dynamic process using remote sensing, enhancing the state prediction accuracy for low-visibility and occlusion scenarios in dynamic scenes. Experimental evaluations in indoor settings confirm the effectiveness of the framework in terms of accuracy and computational efficiency. These results highlight the benefit of integrating stationary LiDAR sensors' state estimates into a switching consensus information filter to enhance the reliability of tracking and to reduce estimation error in the sense of mean square and covariance.
设计了一种分布式状态观测器，用于在分布式激光雷达传感器网络中的动态环境和遮挡情况下对移动机器人进行状态估计和跟踪。所提出的新颖框架利用基于共识的信息滤波器和感兴趣区域来增强三维边界框检测和跟踪，以用于移动机器人的状态估计。该框架能够利用遥感识别动态过程的输入，提高动态场景中低能见度和遮挡场景下的状态预测精度。室内环境中的实验评估证实了该框架在准确性和计算效率方面的有效性。这些结果突出了将固定激光雷达传感器的状态估计集成到切换共识信息滤波器中的好处，以提高跟踪的可靠性，并在均方和协方差意义上减少估计误差。
