The field of autonomous navigation and perception is rapidly evolving, with a focus on developing innovative solutions for robust and accurate localization, mapping, and object detection. Recent research has explored the use of topological maps, lidar scan matching, and event-based cameras to improve navigation in complex environments. Additionally, there has been a growing interest in addressing security concerns, such as adversarial attacks and sybil-based attacks, which can compromise the reliability of autonomous systems. Noteworthy papers in this area include PRISM-Loc, which proposes a lightweight long-range lidar localization approach, and Adversarial Attacks and Detection in Visual Place Recognition, which analyzes the effect of adversarial attacks on visual place recognition systems. Another notable work is DepthVanish, which introduces a novel stereo depth attack that jointly optimizes both the striped structure and texture elements.