The field of human-robot interaction and manipulation is rapidly evolving, with a focus on developing more intuitive, efficient, and robust systems. Recent research has explored the use of simulation, data augmentation, and sensor fusion to improve the performance of robotic manipulation policies. Additionally, there is a growing interest in understanding the social dynamics of human-robot interactions, including the impact of robot design and height on human compliance. Noteworthy papers in this area include: Right-Side-Out, which introduces a zero-shot sim-to-real framework for garment reversal tasks, achieving up to 81.3% success rate. MagiClaw, which presents a versatile two-finger end-effector that functions interchangeably as a handheld tool and a robotic end-effector, bridging the gap between human demonstration and robotic deployment.