Optimal Motion-Cueing Algorithm Using Motion System Kinematics

Aminzadeh, Masoumeh; Mahmoodi, A.; Sabzehparvar, Mehdi

doi:10.3166/ejc.18.363-375

Cited by 16 publications

(7 citation statements)

References 8 publications

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“…This restriction plays a crucial role in the refinement of the overall operation, ensuring smoother and more accurate machining processes. As a result, the implementation of this optimal motioncueing algorithm contributes to increased efficiency and reduction in defects during the manufacturing of components [29].…”

Section: Introductionmentioning

confidence: 99%

Innovative Approaches to Sustainable Computer Numeric Control Machining: A Machine Learning Perspective on Energy Efficiency

Nugrahanto,

Gunawan,

Chen

2024

Sustainability

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Computer Numeric Control (CNC) five-axis milling plays a significant role in the machining of precision molds and dies, aerospace parts, consumer electronics, etc. This research aims to explore the potential of the machine learning (ML) technique in improving energy efficiency during the CNC five-axis milling process for sustainable manufacturing. The experiments with various machining parameters, forms of toolpath planning, and dry cutting conditions were carried out, and the data regarding energy consumption were collected simultaneously. The relationship between machine parameters and energy consumption was analyzed and built. Subsequently, a machine learning algorithm was developed to classify test methods and identify energy-efficient machining strategies. The developed algorithm was implemented and assessed using different classification methods based on the ML concept to effectively reduce energy consumption. The results show that the Decision Tree and Random Forest algorithms produced lower Root Mean Square Error (RMSE) values of 4.24 and 4.28, respectively, compared to Linear, Lasso, and Ridge Regression algorithms. Verification experiments were conducted to ascertain the real-world applicability and performance of the ML-based energy efficiency approach in an operational CNC five-axis milling machine. The findings not only underscore the potential of ML techniques in optimizing energy efficiency but also offer a compelling pathway towards enhanced sustainability in CNC machining operations. The developed algorithm was implemented within a simulation framework and the algorithm was rigorously assessed using machine learning analysis to effectively reduce energy consumption, all while ensuring the accuracy of the machining results and integrating both conventional and advanced regression algorithms into CNC machining processes. Manufacturers stand to realize substantial energy savings and bolster sustainability initiatives, thus exemplifying the transformative power of ML-driven optimization strategies.

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Section: Introductionmentioning

confidence: 99%

Innovative Approaches to Sustainable Computer Numeric Control Machining: A Machine Learning Perspective on Energy Efficiency

Nugrahanto,

Gunawan,

Chen

2024

Sustainability

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“…Telban and Cardullo [15] found that the angular velocity (AV) and LA are the best control inputs to reach the best motion sensation between the real vehicle and SBMP users. Aminzadeh et al [21] used the inverse velocity kinematics of the Hexapod platform in the optimal MCA to cogitate the position and velocity boundaries of the SBMP's actuators. The position limitations of the SBMP's actuators control directly, while the velocity limitations of the m.r.chalakqazani@gmial.com; Houshyar.asadi@deakin.edu.au; saeid.nahavandi@deakin.edu.au).…”

Section: Introduction Sage Of the Simulation-based Motion Platforms (Sbmps)mentioning

confidence: 99%

“…Mohammad Reza Chalak Qazani, Houshyar Asadi, Member, IEEE, Saeid Nahavandi, Fellow, IEEE An Optimal Motion Cueing Algorithm Using the Inverse Kinematic solution of the Hexapod Simulation Platform U SBMP's actuators control indirectly via the derivative of the actuators' positions. It should be noted that as Aminzadeh et al [21] did not consider the acceleration limitations of the actuators, which are very critical for following the desired motion and regenerating realistic motion signals by the SBMP. Therefore, the proposed method by Aminzadeh et al [21] increased the chance of exceeding the acceleration limitations of actuators when there is a high-speed motion signal.…”

Section: Introduction Sage Of the Simulation-based Motion Platforms (Sbmps)mentioning

confidence: 99%

“…It should be noted that as Aminzadeh et al [21] did not consider the acceleration limitations of the actuators, which are very critical for following the desired motion and regenerating realistic motion signals by the SBMP. Therefore, the proposed method by Aminzadeh et al [21] increased the chance of exceeding the acceleration limitations of actuators when there is a high-speed motion signal. Also, they did not decouple the model, which increases the chance of infeasibility in solving the Riccati equation.…”

Section: Introduction Sage Of the Simulation-based Motion Platforms (Sbmps)mentioning

confidence: 99%

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An Optimal Motion Cueing Algorithm Using the Inverse Kinematic Solution of the Hexapod Simulation Platform

Qazani

Asadi

Nahavandi

2022

IEEE Trans. Intell. Veh.

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“…Because of the workspace limitations of a simulator, an adaptive algorithm was developed by Parrish, Dieudonne, Bowles and Martin in 1975, which is implemented in the frequency domain to eliminate the limited workspace problem. In this algorithm the coefficients are different [13] and motion perception is considered a tracking problem [14]. The acceleration that is obtained from the simulator should be tracked [15].…”

Section: Introductionmentioning

confidence: 99%

Realization of a Desktop Flight Simulation System for Motion-Cueing Studies

Volkaner

Sozen

Omurlu

2016

International Journal of Advanced Robotic Systems

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Parallel robotic mechanisms are generally used in flight simulators with a motion-cueing algorithm to create an unlimited motion feeling of a simulated medium in a bounded workspace of the simulator. A major problem in flight simulators is that the simulation has an unbounded space and the manipulator has a limited one. Using a washout filter in the motion-cueing algorithm overcomes this. In this study, a low-cost six degrees of freedom (DoF) desktop parallel manipulator is used to test a classical motion-cueing algorithm; the algorithm's functionality is confirmed with a Simulink real-time environment. Translational accelerations and angular velocities of the simulated medium obtained from FlightGear flight simulation software are processed through a generated washout filter algorithm and the simulated medium's motion information is transmitted to the desktop parallel robotic mechanism as a set point for each leg. The major issues of this paper are designing a desktop simulation system, controlling the parallel manipulator, communicating between the flight simulation and the platform, designing a motion-cueing algorithm and determining the parameters of the washout filters.

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Optimal Motion-Cueing Algorithm Using Motion System Kinematics

Cited by 16 publications

References 8 publications

Innovative Approaches to Sustainable Computer Numeric Control Machining: A Machine Learning Perspective on Energy Efficiency

Innovative Approaches to Sustainable Computer Numeric Control Machining: A Machine Learning Perspective on Energy Efficiency

An Optimal Motion Cueing Algorithm Using the Inverse Kinematic Solution of the Hexapod Simulation Platform

Realization of a Desktop Flight Simulation System for Motion-Cueing Studies

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