Autors: Komarski, D. P., Diakov, D. I., Vassilev, V. A., Nikolova, H. N. Title: Study of tripod elastic parallel mechanism for mechanical neural network Keywords: DOF, flexures, neural network, Parallel kinematic, positioning, tripodAbstract: This paper presents the design and analysis of 3-Degrees-of-Freedom (3-DOF) tripod elastic parallel mechanism developed as a part of larger surface-shaping mechanical neural network that manipulates multiple of these elastic tripods. While traditional rigid-link parallel manipulators offer advantages in stiffness and precision, they are often limited by inherent issues such as friction, backlash, and wear associated with conventional kinematic joints. This proposed structure addresses these limitations by leveraging the inherent flexibility and controlled deformation of compliant elements, typically realized through flexure hinges, to achieve three degrees of freedom (e.g., one translational and two rotational motions) without the need for discrete joints. The compliant nature of the tripod facilitates monolithic structure, leading to enhanced repeatability and reduced assembly complexity. References - Deliyski R., Virtual Measurement System for Length Measurement Based on Visual-Inertial Odometry, (2020) 30th International Scientific Symposium Metrology and Metrology Assurance, MMA 2020. DOI: 10.1109/MMA49863.2020.9254258
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