It is essential for a successful completion of a robot object grasping and manipulation task to accurately sense the manipulated object’s pose. Typically, computer vision is used to obtain this information, but it may not be available or be reliable in certain situations. This paper presents a global optimisation method where tactile and force sensing together with the robot’s proprioceptive data are used to find an object’s pose. This method is used to either improve an estimate of the object’s pose given by vision or globally estimating it when no vision is available. Results show that the proposed method consistently improves an initial estimate (e.g. from vision) and is also able to find the object’s pose without any prior estimate. To demonstrate the performance of the algorithm, an experiment is carried out where the robot is handed a small object (a pencil) and inserts it into a narrow hole without any use of vision.


    Access

    Download


    Export, share and cite



    Title :

    Global estimation of an object’s pose using tactile sensing



    Publication date :

    2015-03-23


    Remarks:

    Bimbo , J M , Kormushev , P , Althoefer , K A & Liu , H 2015 , ' Global estimation of an object’s pose using tactile sensing ' , Advanced Robotics , vol. 29 , no. 5 , pp. 363-374 . https://doi.org/10.1080/01691864.2014.1002531



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    004 / 629



    Tactual Imaging of Object's Surfaces Using a Tactile Sensor

    Kinoshita, G. / Irie, T. / Tanie, K. | British Library Online Contents | 1995


    Unmixing Space Object's Moderate Resolution Spectra

    Dao, P. | British Library Conference Proceedings | 2014


    Stable grasping under pose uncertainty using tactile feedback

    Dang, H. | British Library Online Contents | 2014


    Pose-and-shear-based tactile servoing

    Lloyd, John A / Lepora, Nathan F | BASE | 2024

    Free access

    Vision-based Object’s Shape Determination for Robot Alignment

    Azman, Farah Adiba / Daud, Mohd Razali / Mohamed, Amir Izzani et al. | BASE | 2018

    Free access