PaperForward kinematics solution of Stewart platform using neural networks
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Validation of a Stewart platform inspection system with an artificial neural network controller
2022, Precision EngineeringCitation Excerpt :The application of ANNs for Stewart Platforms can be very useful in different ways. As shown in different studies, the modelling of the Stewart Platform dynamics [26] and kinematics [27] can simulate the Stewart Platform accurately. In the modelling process, it is important to design an appropriate ANN structure, i.e., number of neurons in hidden layers, to represent the system successfully [28].
Forward and inverse kinematics of a 5-DOF hybrid robot for composite material machining
2020, Robotics and Computer-Integrated ManufacturingCitation Excerpt :In general, the direct kinematic equations are a set of nonlinear equations and certain elimination methods such as wu-elimination method [6], Sylvester's dialytic elimination [7] and other special elimination method [8], are utilized to transfer the equations to be a polynomial equation with a single unknown. The most general polynomial equation is an 8th-, 16th- or higher order equation, which in turn has to be solved by some numerical methods such as Taylor series expansion [9], neural networks strategies [10,11], and Newton classical methods [12]. For example, Geng et al. used neural networks to find the forward kinematics solution of Stewart platform [13].
Real time direct kinematic problem computation of the 3PRS robot using neural networks
2018, NeurocomputingCitation Excerpt :Finally, in the literature very few works analyze the Real-Time performance of DKP solving ANNs [19]. In [14,16], the time performance of the selected MLPs used to solve the DKP of parallel robots is detailed and compared with traditional NR approaches, resulting in a decrease in an order of magnitude on the computational time. However, these measures are carried out with a particular test trajectory, and only consider the final network architecture, and do not analyze the effect of network size in the time performance.
PhyNRnet: Physics-Informed Newton–Raphson Network for Forward Kinematics Solution of Parallel Manipulators
2024, Journal of Mechanisms and Robotics