Localization Error

Localization error, the discrepancy between a system's estimated and true location, is a critical challenge across various applications, from autonomous vehicles to UAV navigation. Current research focuses on quantifying the impact of this error on system performance, particularly in challenging environments, and developing robust algorithms like Iterative Closest Point (ICP) to mitigate its effects, often incorporating techniques like optimal transport theory for data fusion. This work is crucial for improving the safety and reliability of autonomous systems, as evidenced by studies demonstrating the significant influence of localization error on factors such as maximum safe speed and the accuracy of object detection. Furthermore, research highlights the limitations of existing metrics like Intersection over Union (IoU) for evaluating localization accuracy, underscoring the need for more comprehensive evaluation methods.