Automation has led to industrial robots facilitating a wide array of high speed, endurance, and precision operations undertaken in the manufacturing industry today. An acceptable level of functioning and control is therefore vital to the efficacy and successful implementation of such manipulators. This research presents a comprehensive analytical tool for downstream optimization of manipulator design, functionality, and performance. The proposed model is reconfigurable and allows for modelling and validation of different industrial robots. Unique 3D visual models for a manipulator workspace and kinematic singularities are developed to gain an understanding into the task space and reach conditions of the manipulator's end-effector. The developed algorithm also presents a non-conventional and computationally inexpensive solution to the inverse kinematics problem through the use Artificial Neural Networks. Application of the proposed technique is further extended to aid in development of path planning models for a uniform, continuous, and singularity free motion.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Reconfigurable Validation Model for Identifying Kinematic Singularities and Reach Conditions for Articulated Robots and Machine Tools


    Beteiligte:
    Aggarwal, Luv (Autor:in)

    Erscheinungsdatum :

    2014-01-01


    Anmerkungen:

    Electronic Theses and Dissertations


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629






    Reconfigurable Model Predictive Control for Articulated Vehicle Stability With Experimental Validation

    Zhang, Yubiao / Khajepour, Amir / Hashemi, Ehsan et al. | IEEE | 2020


    Kinematic Design of Modular Reconfigurable In-Parallel Robots

    Yang, G. / Chen, I.-M. / Lim, W. K. et al. | British Library Online Contents | 2001


    Baxter Kinematic Modeling, Validation and Reconfigurable Representation

    Djuric, Ana M. / e Silva, Lucas / Marques, Mairon et al. | SAE Technical Papers | 2016