We propose an algorithm for decentralised navigation of multiple independent agents, applicable to Robotics and Air Traffic Control (ATC). We present completely decentralised Navigation Functions that are used to build potential fields and consequently feedback control laws. Our approach employs local sensing, limited by a maximum sensing range and integrates priorities in the Navigation Function (NF) construction. Static and moving obstacles are taken into account, as well as agents that are unable to maneuver. A decentralised feedback control law is used, based on the gradient of the potential field, ensuring convergence and collision avoidance for all agents while respecting a lower velocity bound. An upper limit for the convergence time is given and simulation results are presented to demonstrate the efficacy of the proposed algorithm.