scholarly journals Optimal motion cueing algorithm for accelerating phase of manned spacecraft in human centrifuge

2020 ◽  
Vol 33 (7) ◽  
pp. 1991-2001
Author(s):  
Ali MAHMOODI ◽  
Isooda KAZEMI
Keyword(s):  
Optimal Motion ◽  
Manned Spacecraft ◽  
Motion Cueing

Optimal motion cueing for 5-DOF motion simulations via a 3-DOF motion simulator

2009 ◽  
Vol 17 (1) ◽  
pp. 170-184 ◽  
Author(s):  
Yang-Hung Chang ◽  
Chung-Shu Liao ◽  
Wei-Hua Chieng
Keyword(s):  
Optimal Motion ◽  
Motion Simulator ◽  
Motion Cueing

Optimal Motion-Cueing Algorithm Using Motion System Kinematics

2012 ◽  
Vol 18 (4) ◽  
pp. 363-375 ◽  
Author(s):  
Masoumeh Aminzadeh ◽  
Ali Mahmoodi ◽  
Mehdi Sabzehparvar
Keyword(s):  
Optimal Motion ◽  
Motion System ◽  
Motion Cueing

A novel motion cueing algorithm integrated multi-sensory system–Vestibular and proprioceptive system

2019 ◽  
Vol 234 (2) ◽  
pp. 256-271
Author(s):  
Pham Duc-An ◽  
Nguyen Duc-Toan
Keyword(s):  
Visual Motion ◽  
Driving Simulator ◽  
Sensory System ◽  
Lateral Acceleration ◽  
Optimal Motion ◽  
Tilted Angle ◽  
Motion Cueing ◽  
Simulated Motion ◽  
S Curve ◽  
The Mathematical Model

Motion cueing algorithms are used to produce a motion which feels as realistic as possible while remaining in the limited workspace of driving simulators. Several optimal motion cueing algorithms were developed to improve both the exploitation of the workspace of a driving simulator and the realistic of the simulated motion. In the dynamics model of the optimal motion cueing algorithms, several kinds of motion-sensory systems are integrated to optimize the simulated motion sensation. However, most previous works have just focused on the visual and vestibular system. The mathematical model of the proprioceptive system, that also senses the non-visual motion, has rarely been concerned. In this paper, a novel optimal motion cueing algorithm, which integrates model of the proprioceptive system, is developed to reduce the false cues from muscle spindle of head/neck system sensing lateral tilted angle. The optimal motion cueing algorithm has a significant effect on the pilot's perception when the tilted angle is rather large. An example of the simulation of a roller coaster running along a planar S-curve trajectory with only lateral acceleration is investigated with current motion cueing algorithms and optimal motion cueing algorithm. Several objective criteria were introduced to evaluate the simulated perception of all investigated motion cueing algorithms. The results demonstrate that optimal motion cueing algorithm is better than current motion cueing algorithms in most criteria and also sub-criteria.

scholarly journals Optimal Motion Cueing Algorithm Using the Human Body Model.

2002 ◽  
Vol 45 (2) ◽  
pp. 487-491 ◽  
Author(s):  
Myung-Chul HAN ◽  
Hyung-Sang LEE ◽  
Suk LEE ◽  
Man Hyung LEE
Keyword(s):  
Human Body ◽  
Human Body Model ◽  
Optimal Motion ◽  
Body Model ◽  
Motion Cueing

scholarly journals Optimal Motion Cueing for Race Cars

2016 ◽  
Vol 24 (1) ◽  
pp. 200-215 ◽  
Author(s):  
Ingrid G. Salisbury ◽  
David J. N. Limebeer
Keyword(s):  
Optimal Motion ◽  
Motion Cueing ◽  
Race Cars

A genetic algorithm–based nonlinear scaling method for optimal motion cueing algorithm in driving simulator

2018 ◽  
Vol 232 (8) ◽  
pp. 1025-1038 ◽  
Author(s):  
Houshyar Asadi ◽  
Chee Peng Lim ◽  
Arash Mohammadi ◽  
Shady Mohamed ◽  
Saeid Nahavandi ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Driving Simulator ◽  
Linear Acceleration ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Optimal Motion ◽  
Scaling Method ◽  
Motion Cueing ◽  
Physical Limitations ◽  
Simulator Motion

A motion cueing algorithm plays an important role in generating motion cues in driving simulators. The motion cueing algorithm is used to transform the linear acceleration and angular velocity of a vehicle into the translational and rotational motions of a simulator within its physical limitation through washout filters. Indeed, scaling and limiting should be used along within the washout filter to decrease the amplitude of the translational and rotational motion signals uniformly across all frequencies through the motion cueing algorithm. This is to decrease the effects of the workspace limitations in the simulator motion reproduction and improve the realism of movement sensation. A nonlinear scaling method based on the genetic algorithm for the motion cueing algorithm is developed in this study. The aim is to accurately produce motions with a high degree of fidelity and use the platform more efficiently without violating its physical limitations. To successfully achieve this aim, a third-order polynomial scaling method based on the genetic algorithm is formulated, tuned, and implemented for the linear quadratic regulator–based optimal motion cueing algorithm. A number of factors, which include the sensation error between the real and simulator drivers, the simulator’s physical limitations, and the sensation signal shape-following criteria, are considered in optimizing the proposed nonlinear scaling method. The results show that the proposed method not only is able to overcome problems pertaining to selecting nonlinear scaling parameters based on trial-and-error and inefficient usage of the platform workspace, but also to reduce the sensation error between the simulator and real drivers, while satisfying the constraints imposed by the platform boundaries.

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