The main objective of any motion cueing algorithm is to represent the acceleration of a simulated aircraft as good as possible. The main constraint is the space envelope the motion system is able to reach. Reaching this limit inevitably leads to a sudden change of the current movement and the pilot faces an unexpected and therefore disturbing acceleration. As a consequence, any cueing algorithm has to be parametrized in a way to prevent the motion system from touching the limits of the usable space. If, for any reason, this is not possible e. g. due to inadequate pilot actions or unforeseen simulator operations a strategy to avoid false cues as good as possible needs to be implemented. This implies that the limits are known. Unfortunately, calculating the platform position by using a set of actuator lengths for a parallel robotic system like a hexapod motion ends up in an iterative process. Therefore, most current limiting functions refer to the actuator states to decide whether the platform is approaching a limit or not. The problem with this method is that reaching the limit of an actuator does not imply which degrees of freedom of the entire system are affected. In some cases, it is even not possible to decide which direction of a degree of freedom needs to be limited. In order to tackle this deficiency this paper proposes a non-iterative method to calculate the current space limits for all six degrees of freedom using the current platform position and the lengths of the fully extended and retracted actuators. Based on this information it is possible to restrict the movement of the motion in the affected degree of freedom in case the platform approaches a limit. Two limiting functions, one for translational and one for rotational degrees of freedom are given. Finally, the effectiveness of the proposed limiting functions is demonstrated for a rejected take-off run due to an engine failure before the decision speed V1. This is both, a common and an aggressive maneuver for aircraft training simulators.