False cue influence on motion cue quality for 10 motion cueing algorithms

Abstract

Motion simulators are becoming increasingly popular for many applications in which human sensation is important to replicate and optimize target motions. For the emulation of the perceived human acceleration, motion cueing algorithms (MCAs) have been proposed in the literature that mimics the motion sensation by a combination of actual acceleration and tilted gravity effects, termed g-force or specific force. However, their relative performance has not yet been analyzed. This paper reviews existing families of MCAs and compares their performance for a simple offline S-shaped planar test trajectory featuring only lateral acceleration. The comparison is carried out both numerically using two previously published objective measures, the “performance indicator” of Pouliot, Gosselin, and Nahon, and the “good criterion” of Schmidt, as well as subjectively by a preliminary passenger rating on a real motion platform—Robocoaster testbed. The results show that (a) the novel optimizing MCA group exploits more effectively the workspace of the motion platform than the traditional MCA group for reducing false cue with small scale error and shape errors, (b) path-dependent tuning of MCA parameters may improve motion sensation, (c) average subjective ratings can be made to correlate well with the “good criterion” when expanded with a penalty for false angular velocity cues, and (d) the scale error of specific force seems to play the most important role to the evaluation of test subject on the motion cue quality. However, still a strong variance in subjective ratings was observed, making further research necessary.

Novel model predictive control-based motion cueing algorithm for compensating centrifugal acceleration in KUKA robocoaster-based driving simulators

“…The variables α m i n 0.25em and α m a x 0.25em define the limitations on the angular rotation within the motion platform's workspace. 16…”

“…The variables α min and α max define the limitations on the angular rotation within the motion platform's workspace. 16 Additionally, other constraint conditions for input and output variables (as displayed in Table 1) have been carefully selected to restrict abrupt changes in simulated acceleration and ensure the maximum simulated specific force remains within acceptable bounds during the simulation task.…”

“…For example, in the case of the KUKA Robocoaster-based motion platform, ten motion cueing algorithms were thoroughly investigated and adapted using a conversion process to address the roll/sway problem. 16 The process begins by generating the desired lateral acceleration through the motion cueing algorithms. Subsequently, in the conversion process, the target signals are fed into an MCA to generate simulated signals, including linear acceleration and roll angle.…”

“…In the comparative study of ten Motion Cueing Algorithm (MCA) implementations, 16 the Linear Model Predictive Control (MPC) algorithm is also applied to simulation tasks involving only lateral acceleration. However, due to the non-linear relationship between centrifugal acceleration (as depicted in equation 2 ) and yaw angular acceleration, constructing a linear model control system for MPC encompassing both longitudinal/pitch and lateral/roll channels becomes challenging.…”

A Review of Dynamic Vehicular Motion Simulators: Systems and Algorithms

“…However, these strategies could generate the perception of false cues due to imperfections and consequently do not match the visual stimulation [36]. These false cues generate fatigue and discomfort in the operator.…”