The field of robotics is rapidly advancing, with a focus on developing more sophisticated human-robot interaction and autonomous systems. Recent research has highlighted the importance of creating more flexible and adaptable robotic systems that can learn from humans and interact with their environment in a more natural way. One of the key directions in this area is the development of modular and plug-and-play robotic systems that can be easily customized and controlled using a variety of input devices. Another significant trend is the integration of machine learning and computer vision techniques to enable robots to learn from demonstration and improve their performance over time. Additionally, there is a growing interest in developing autonomous systems that can operate in complex and dynamic environments, such as surgical settings, and perform tasks that require precision and dexterity. Noteworthy papers in this area include: PAPRLE, which introduces a modular ecosystem for robotic limbs that enables flexible placement and control. AURA-CVC, which proposes an end-to-end robotic-ultrasound-guided pipeline for central venous catheterization. ULC, which demonstrates a unified and fine-grained controller for humanoid loco-manipulation that can achieve a combination of tracking accuracy, large workspace, and robustness.