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Full-Text Articles in Engineering
Development Of Prediction Method For Dimensional Stability Of 3d-Printed Objects, Kyung-Eun Min, Jae-Won Jang, Jesik Shin, Cheolhee Kim, Sung Yi
Development Of Prediction Method For Dimensional Stability Of 3d-Printed Objects, Kyung-Eun Min, Jae-Won Jang, Jesik Shin, Cheolhee Kim, Sung Yi
Mechanical and Materials Engineering Faculty Publications and Presentations
Fused deposition modeling (FDM), as one of the additive manufacturing processes, is known for strong layer adhesion suitable for prototypes and end-use items. This study used a multiple regression model and statistical analysis to explore the dimensional accuracy of FDM objects. Factors such as inclination angle, layer thickness, support space, and raster angle were examined. Machine learning models (Gaussian process regression (GPR), support vector machines (SVM), and artificial neural network (ANN)) predicted dimensions using 81 datapoints. The mean squared dimensional error (MSDE) between the measured and designed surface profiles was selected as an output for the dimensional accuracy. Support spacing, …
Biomechanical And Sensory Feedback Regularize The Behavior Of Different Locomotor Central Pattern Generators, Kaiyu Deng, Alexander J. Hunt, Nicholas Szczecinski, Matthew Tresch, Hillel J. Chiel, Charles Heckman, Roger Quinn
Biomechanical And Sensory Feedback Regularize The Behavior Of Different Locomotor Central Pattern Generators, Kaiyu Deng, Alexander J. Hunt, Nicholas Szczecinski, Matthew Tresch, Hillel J. Chiel, Charles Heckman, Roger Quinn
Mechanical and Materials Engineering Faculty Publications and Presentations
This work presents an in-depth numerical investigation into a hypothesized two-layer central pattern generator (CPG) that controls mammalian walking and how different parameter choices might affect the stepping of a simulated neuromechanical model. Particular attention is paid to the functional role of features that have not received a great deal of attention in previous work: the weak cross-excitatory connectivity within the rhythm generator and the synapse strength between the two layers. Sensitivity evaluations of deafferented CPG models and the combined neuromechanical model are performed. Locomotion frequency is increased in two different ways for both models to investigate whether the model’s …
A Functional Subnetwork Approach To Designing Synthetic Nervous Systems That Control Legged Robot Locomotion, Nicholas Szczecinski, Alexander J. Hunt, Roger Quinn
A Functional Subnetwork Approach To Designing Synthetic Nervous Systems That Control Legged Robot Locomotion, Nicholas Szczecinski, Alexander J. Hunt, Roger Quinn
Mechanical and Materials Engineering Faculty Publications and Presentations
A dynamical model of an animal’s nervous system, or synthetic nervous system (SNS), is a potentially transformational control method. Due to increasingly detailed data on the connectivity and dynamics of both mammalian and insect nervous systems, controlling a legged robot with an SNS is largely a problem of parameter tuning. Our approach to this problem is to design functional subnetworks that perform specific operations, and then assemble them into larger models of the nervous system. In this paper, we present networks that perform addition, subtraction, multiplication, division, differentiation, and integration of incoming signals. Parameters are set within each subnetwork to …
Development And Training Of A Neural Controller For Hind Leg Walking In A Dog Robot, Alexander J. Hunt, Nicholas Szczecinski, Roger Quinn
Development And Training Of A Neural Controller For Hind Leg Walking In A Dog Robot, Alexander J. Hunt, Nicholas Szczecinski, Roger Quinn
Mechanical and Materials Engineering Faculty Publications and Presentations
Animals dynamically adapt to varying terrain and small perturbations with remarkable ease. These adaptations arise from complex interactions between the environment and biomechanical and neural components of the animal’s body and nervous system. Research into mammalian locomotion has resulted in several neural and neuro-mechanical models, some of which have been tested in simulation, but few “synthetic nervous systems” have been implemented in physical hardware models of animal systems. One reason is that the implementation into a physical system is not straightforward. For example, it is difficult to make robotic actuators and sensors that model those in the animal. Therefore, even …