This paper proposes a navigation algorithm that considers the states of humans and robots in order to achieve harmonious coexistence between them. A robot navigation in the presence of humans and other robots is rarely considered in the field of robotics. When navigating through a space filled with humans and robots with different functions, a robot should not only pay attention to obstacle avoidance and goal seeking, it should also take into account whether it interferes with other people or robots. To deal with this problem, we propose several harmonious rules, which guarantee a safe and smooth navigation in a human-robot environment. Based on these rules, a practical navigation method-human-centered sensitive navigation (HCSN)-is proposed. HCSN considers the fact that both humans and robots have sensitive zones, depending on their security regions or on a human's psychological state. We model these zones as various sensitive fields with priorities, whereby robots tend to yield socially acceptable movements.

An enhanced adaptive sliding mode fuzzy approach is applied to control the position and load swing of a 3D overhead crane system. The merits of this method include the robustness and model free properties of the sliding mode and fuzzy logic controllers, respectively. An adaptable slope of sliding surface is presented and the chattering phenomenon of sliding mode control is also discussed to enhance the control performance. Furthermore, this paper provides a compensating algorithm to the control deadzone of overhead crane system. At last, several simulation results demonstrate the effectiveness.