In this project, a novel human friendly mobile robot navigation controller is investigated. By applying this controller, the mobile robot is able to work in a complicated environment with several humans and other obstacles avoiding them before a collision happens. This robot will have a preference in avoiding humans over other obstacles keeping human safety as its first consideration. To achieve this goal, three problems have to be solved. The first one is the robot should be able to “see” the environment and distinguish the human and the obstacles. The functions of human sensor and sonar sensor are presented. A new sensor fusion method for combining the information collected by these two sorts of sensors based on Dempster-Shafer evidence theory is also proposed. By using the sensor fusion method, the robot will have a better view of human. The second problem is the robot has to know how to avoid collision. A new navigation algorithm, based on an improved velocity potential field method, is then described. The way of calculating the distances of avoidance based on different kinds of obstacles is presented as well. The last problem is how to make the mobile robot put human as its first priority when avoiding collision. A summary of the methods which are used to protect human is mentioned. According to the simulation and the experimental results, the new mobile robot navigation controller successfully led the robot avoid collisions in complicated situations and always put human safety as its first consideration.