Incorporating Human Perception With the Motion Washout Filter Using Fuzzy Logic Control

Asadi, Houshyar; Mohamed, Shady; Nahavandi, Saeid

doi:10.1109/tmech.2015.2405934

Cited by 64 publications

(24 citation statements)

References 18 publications

(19 reference statements)

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“…Also, CC shows the shape following the sameness of the motion feeling between the drivers of the SBMP and the real car. Asadi et al [2,17] employed CC in MCA domain as an essential factor to evaluate the motion feeling of MCA. The range of the CC is between -1 and 1 while one shows the identical shape sameness between two signals.…”

Section: Resultsmentioning

confidence: 99%

“…The second generation of the MCA is called adaptive MCA that varies the fixed parameters of the classical MCA [12]. Recently, different types of adaptive MCAs using the fuzzy logic control [13][14][15] are developed while considering the human vestibular system aiming to deliver the realistic motion feeling [16][17][18]. The linear quadratic regulator technique by considering of human vestibular to decrease the human feeling error is employed in forming of optimal MCA [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

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A Motion Cueing Algorithm Based on Model Predictive Control Using Terminal Conditions in Urban Driving Scenario

Qazani

Asadi

Nahavandi

2021

IEEE Systems Journal

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The motion cueing algorithm (MCA) is in charge of the real vehicle motion feeling regeneration for the driver of the simulation-based motion platform (SBMP) with respect to its limitations. The model predictive control (MPC) has newly employed in developing MCAs to calculate the optimal input signals for delivering the best motion feeling to the SBMP's drivers while respecting the boundaries of the platform. The stability of the MCA based on MPC has become one of the main issues for some scenarios such as urban driving scenario which involves sudden decelerations/accelerations (stop and start moving), sharp and large turn, slalom movement. The urban driving scenario destabilises the current MCA based on MPC and leads undesired motion fluctuations which creates unpleasant motion artefact for the SBMP drivers. Therefore, the displacement of the SBMP should be penalised conservatively to respect the workspace boundaries for all driving scenarios. This will make the motion conservative and can cause some motion feeling error. In this paper, the concept of terminal conditions (weights and states) are employed for the first time to design and develop a new generation of MCA based on MPC to enhance the performance of the model for different scenarios such as the heavy-traffic scenario in urban areas. Also, the stability of the MPC by considering of the terminal conditions is investigated in MCA domain. Then, the MCA based on MPC by considering of terminal conditions is developed using MATLAB software with presentation of urban motion scenario. The outcomes demonstrate the effectiveness of the designed model with common MCA based on MPC without consideration of the terminal conditions.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Motion Cueing Algorithm Based on Model Predictive Control Using Terminal Conditions in Urban Driving Scenario

Qazani

Asadi

Nahavandi

2021

IEEE Systems Journal

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“…In order to achieve more realistic acceleration and angular velocity stimulation in limited motion space, washout algorithm is introduced. Here we adopt the improved washout algorithm [19] to achieve better vestibular stimulation which will not go further elaboration.…”

Section: Figure 6 Location Of the Center Of Gravity Corresponding To mentioning

confidence: 99%

Application of Optimal-Jerk Trajectory Planning in Gait Balance Training Robot

Fu¹,

Chen²,

X³

et al. 2020

Preprint

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Aiming at the gait and balance disorder of the elderly with the increase of age and the occurrence of various senile diseases, this paper proposes a novel gait balance training robot (G-Balance) based on a 6-DOF parallel platform. Based on the platform movement and IMU wearable sensors, two training modes, active and passive, have been developed to achieve vestibular stimulation. Virtual reality technology is also combined to achieve visual stimulation. In the active training mode, the elderly actively exercise to control the posture change of the platform and the switching of the virtual scene. In the passive training mode, the platform movement is combined with the virtual scene to simulate some bumpy environments such as earthquakes to enhance the human anti-interference ability. In order to achieve smooth switching of the scene, continuous speed and acceleration of the platform motion are required in some scenarios, in which trajectory planning algorithm is applied to meet the requirement. This paper expounds the application of trajectory planning algorithm in balance training mode.

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“…The movement signals of the real vehicle cannot be directly implemented into the SBMP because of the limited workspace area. The approach to reproduce the real vehicle motion signals (including linear acceleration and angular velocity), generating the same real vehicle movement feeling for the SBMP user, is called motion cueing algorithm (MCA) including classical [11,12], adaptive [13][14][15][16][17][18], optimal [19][20][21][22][23] and model predictive control [24][25][26][27][28]. The classical MCAs are very popular in industries and research centres because of its simplicity, easy tunning, low computational load and safety.…”

Section: Introductionmentioning

confidence: 99%

A New Fuzzy Logic Based Adaptive Motion Cueing Algorithm Using Parallel Simulation-Based Motion Platform

Qazani

Asadi

Bellmann

et al. 2020

2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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Parallel manipulators are recently used in most motion simulation laboratories as they can easily generate six degrees of freedom motion. Recently, fuzzy logic-based adaptive motion cueing algorithms (MCAs) have been employed to reproduce the motion signals. The usage of fuzzy logicbased adaptive MCA reduces the movement sensation error between the real vehicle and the simulation-based motion platform (SBMP) user considering the end-effector limitations in Cartesian space.. In this paper, a new fuzzy logic-based adaptive MCA is introduced to generate motion signals based on the joints' limitations and the movement sensation error between the real vehicle and the SBMP user. Considering the parallel SBMP, joint limits enhance the ability of the introduced adaptive motion cueing algorithm to generate more accurate movement feelings with high fidelity. The simulation results prove that the proposed adaptive motion cueing algorithm can effectively use the large workspace of the parallel SBMP whilst reducing the motion sensation error.

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Incorporating Human Perception With the Motion Washout Filter Using Fuzzy Logic Control

Cited by 64 publications

References 18 publications

A Motion Cueing Algorithm Based on Model Predictive Control Using Terminal Conditions in Urban Driving Scenario

A Motion Cueing Algorithm Based on Model Predictive Control Using Terminal Conditions in Urban Driving Scenario

Application of Optimal-Jerk Trajectory Planning in Gait Balance Training Robot

A New Fuzzy Logic Based Adaptive Motion Cueing Algorithm Using Parallel Simulation-Based Motion Platform

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