Kyle Nelson

Deakin University, Institute for Intelligent Systems Research and Innovation (IISRI), Post-Doc

Deakin University, Centre for Intelligent Systems Research, Post-Doc

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Kyle Nelson received the B.Eng. (hons.) degree in Mechatronics and Robotics in 2009, and the Ph.D. degree in computer vision/image processing in 2013 from Deakin University, Australia, where he attended as a Dean’s Scholar and was a recipient of both the Alfred Deakin Medal and Vice-Chancellor’s Prize. His PhD research focused on the image enhancement technique of super-resolution and combining this concept with ideas from the field of multi-view geometry to produce high-resolution images of 3-dimensional scenes. Currently a research fellow with the Centre for Intelligent Systems Research at Deakin University, Kyle is actively involved in robot-based motion simulation, computer vision and image processing research. Kyle has worked on a number of industry-linked robotics projects including the design and development of a vision-based measurement system for Boeing Research & Technology Australia.

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Papers by Kyle Nelson

Directional and Sectional Ride Comfort Estimation using an Integrated Human Biomechanical-Seat Foam Model

In the methodology of objective measurement of ride comfort, application of a Human Biomechanical... more In the methodology of objective measurement of ride comfort, application of a Human Biomechanical Model (HBM) is valuable for Whole Body Vibration (WBV) analysis. In this study, using a computational Multibody System (MBS) approach, development of a 3D passive HBM for a seated human is considered. For this purpose, the existing MBS-based HBMs of seated human are briefly reviewed first. The Equations of Motion (EoM) for the proposed model are then obtained and the simulation results are shown and compared with idealised ranges of experimental results suggested in the literature. The human-seat interaction is established using a nonlinear vibration model of foam with respect to the sectional behaviour of the seat foam. The developed system is then used for ride comfort estimation offered by a ride dynamic model. The effects of human weight, road class, and vehicle speed on the vibration of the human body segments in different directions are studied. It is shown that the there is a high correlation (more than 99.2%) between the vibration indices of the proposed HBM-foam model and the corresponding ISO 2631 WBV indices. In addition, relevant ISO 2631 indices that show a high correlation with the directional vibration of the head are identified.

On the Simulation-based Objective Estimation of Road Vehicle Ride Comfort

Ride comfort is essential for the road vehicles due to the customer demand in the current automot... more Ride comfort is essential for the road vehicles due to the customer demand in the current automotive industry. Assessment of ride comfort is required to evaluate and improve human comfort in the car. Objective assessment of ride comfort considerably helps to reduce the cost, time, and risk compared to the subjective assessment which requires actual road tests. In this paper, design and implementation of equivalent digital filters for ISO 2631 and 5349 weighting factors are performed. Furthermore, a 3D passive MBS-based Human Biomechanical Model (HBM) of a seated human is proposed for the objective assessment of ride comfort. These two developments are then used for estimation of ride comfort for a ride dynamic model. Comparison between the result obtained from the ISO standard and the proposed HBM shows the usability of the proposed HBM for vehicular comfort studies.

DSC 2015 Europe Germany An Optimal Washout Filter Based on Genetic Algorithm Compensators for Improving Simulator Driver Perception

by Shady Mohamed and Kyle Nelson

– A simulator motion platform cannot exactly reproduce the longitudinal and rotational motions ex... more – A simulator motion platform cannot exactly reproduce the longitudinal and rotational motions experienced in a real vehicle as it is constrained by its physical limits. The aim of this research is to provide an optimal Motion Cueing Algorithm (MCA) that can generate the most realistic motions and high fidelity vehicle accelerations and angular velocities, within the simulator's physical limitations. The optimal washout filter based on Linear Quadratic Regulator (LQR), which takes the recent vestibular system mathematical model and simulator motion in to account, has been proposed to constrain the human perception error between the simulator and real driving, within the limits of the platform motion. This paper presents a new strategy based on optimal control theory and the Genetic Algorithm (GA) to reproduce a signal that can closely follow the reference signal and avoid false motion cues. An optimization method for adjusting the obtained optimal washout filter transfer functions, based on genetic algorithms is used. Three additional compensatory linear blocks are integrated into the LQR-based optimal washout filter, to be tuned based on GA in order to modify the performance of the filters and minimize the fitness value if increasing the order is required. This is achieved by taking a series of factors into account, including: the vestibular sensation error between real and simulated cases; the human threshold limiter in tilt coordination; the human sensation error fluctuation; and cross correlation coefficient; where the effects of these aspects have been previously ignored. The proposed optimized motion cueing algorithm based on compensators using GA is implemented in the MATLAB/Simulink software packages. The results show the superiority of the proposed method due to its better increased performance, enhanced motion fidelity, improved human sensation, and reduced workspace usage compared to previous optimal washout filters.

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