A Nonlinear Motion Cueing Algorithm With a Human Perception Model
Abstract
The objective of a motion system, when used in conjunction with a visual system,
is to stimulate the pilot so that he can perceive the required motion cues necessary to fly
the simulator within the same performance and control activity as the aircraft. An
example of a motion system is the six-degree-of-freedom hexapod shown in Figure E.l.
Platform motion allows the pilot to react more quickly to simulated aircraft
motion as compared to visual stimuli alone, thus enabling him to co1Tect (and reduce the
magnitude) of any deviation sooner than having to wait for the information visually.
Without motion cues the pilot's perception of the simulated vehicle motion is degraded
and the aircraft response feels slower.
The vehicle simulation structure for a motion system is shown in Figure E.2. The
operator control inputs drive a mathematical model of the vehicle dynamics, generating
the vehicle states. The desired motion cues and platform states are produced by passing
the vehicle states through the motion cueing algorithm. The desired platform states are
then transformed from degree-of-freedom space to actuator space, generating the desired
commands to the six actuators. The actuator motion commands serve as input to the
closed-loop platform dynamics, resulting in actual simulator motion.
The motion cueing algorithm generates the desired motion cues that are
constrained within the physical limits of the motion system. The magnitude of the cues is
reduced by scaling and limiting the vehicle states. The duration of the cues is limited by
a technique known as washout. Washout involves returning the platform state to a
neutral position following the initial, or "onset" portion of a motion cue, thus "washing
out" the resulting cue at levels below the pilot's perceptual threshold. This is
accomplished by passing the vehicle state through a high-pass filter, removing long-duration (low-frequency) motion components. Figure E.3 shows the response of a
washout filter to an acceleration ramp to step input. Early approaches to washout
filtering used simple (first- and second-order) linear filters in which the ratio of onset to
washout duration was fixed. Nonlinear approaches were later developed where this ratio
varied with time.
The otolith organs in the human vestibular system sense both acceleration and
tilting of the pilot's head with respect to the gravity vector. Since the otoliths cannot
discriminate between acceleration and tilt, this phenomenon, known as tilt coordination,
can be used to advantage in motion simulation. For long-term specific force simulation,
acceleration cues simulated by high-pass washout filters are augmented by tilting the
motion platform at a rate below the pilot's perceptual threshold. This additional cue
results from passing the vehicle acceleration through a low-pass filter to produce the
desired long-duration tilt cue. Tilt coordination is implemented in a motion cueing
algorithm by adding additional filters in the longitudinal (pitch/surge) and lateral
(roll/sway) modes that produce the additional cues. For this reason four separate modes
are implemented in a motion cueing alg01ithm: longitudinal, lateral, yaw, and heave.