The field of robotics and sensor integration is moving towards more sophisticated and robust systems, with a focus on enhancing accuracy and reliability in challenging environments. Recent developments have seen the integration of multiple sensor modalities, such as visual, inertial, and acoustic sensors, to improve navigation and mapping capabilities. Additionally, there has been a push towards more autonomous systems, with the development of novel control frameworks and algorithms that enable robots to operate effectively in complex and dynamic environments. Noteworthy papers in this area include: Underwater Visual-Inertial-Acoustic-Depth SLAM with DVL Preintegration for Degraded Environments, which proposes a novel SLAM system that integrates multiple sensor modalities for robust underwater navigation. EndoSfM3D: Learning to 3D Reconstruct Any Endoscopic Surgery Scene using Self-supervised Foundation Model, which presents a self-supervised monocular depth estimation framework for 3D reconstruction of endoscopic surgery scenes. Localising under the drape: proprioception in the era of distributed surgical robotic system, which introduces a marker-free proprioception method for precise localization of surgical robots under their sterile draping.