The introduction of robots in our daily lives raises a key issue that is "added" to the "standard challenge" of autonomous robots: the presence of humans in the environment and the necessity to interact with them. In the factory, the robot is physically separated and a security distance is always kept from human workers. With this separation, the primary concern in such environments, the "safety", is ensured. However this separation cannot be applied to future applications where the robot will be in a situation where it will have to assist humans. In a scenario where the robot has to move among people, the notion of safety becomes more important and should be studied in every detail. Yet the biggest di erence in these two environments does not come from the definition of their primary concern, the safety, but comes from a secondary concern. In factory, when the safety is ensured, the feasibility of the task gains in importance. The robot's environment is perfectly structured and all the robots are perfectly coordinated in order to accomplish their tasks. On the contrary, the feasibility of the task leaves its place to the "comfort" for an interactive robot. For a robot that physically interacts with humans, accomplishing a task with the expense of human comfort is not acceptable even the robot does not harm any person. The robot has to perform motion and manipulation actions and should be able to determine where a given task should be achieved, how to place itself relatively to a human, how to approach him/her, how to hand the object and how to move in a relatively constrained environment by taking into account the safety and the comfort of all the humans in the environment. In this work, we propose a novel motion planning framework answering these questions along with its implementation into a navigation and a manipulation planner. We present the Human-Aware Navigation Planner that takes into account the safety, the elds of view, the preferences and the states of all the humans as well as the environment and generates paths that are not only collision free but also comfortable. We also present the Human-Aware Manipulation Planner that breaks the commonly used human-centric approaches and allows the robot to decide and take initiative about the way of an object transfer takes place. Human's safety, field of view, state, preferences as well as its kinematic structure is taken into account to generate safe and most importantly comfortable and legible motions that make robot's intention clear to its human partner.