Dynamic force sensing for high-speed robot manipulation using Kalman filtering techniques

Masaru Uchiyama, Kosei Kitagaki

    Research output: Contribution to journalConference articlepeer-review

    11 Citations (Scopus)


    An implementation was made of the theory of dynamic force sensing for high-speed robot manipulation which uses an optimal filtering technique in order to extract the external forces and moments on an end-effector from those measured by a wrist force sensor which are corrupted by the inertial forces and moments on the end-effector. The theory is summarized, and its implementation in its complete nonlinear style to provide for basic offline experiments is described. The experimental data show that the theory works well in extracting the external forces and moments. In a limited linearized style, the theory was applied to a real manipulation task: detecting an object on a planned trajectory by force information. The monitoring of the collision between the end-effector and the object using the force sensor, which usually requires the end-effector to move slowly to reduce the inertial forces and moments, was done successfully, even for fast motion of the end-effector.

    Original languageEnglish
    Pages (from-to)2147-2152
    Number of pages6
    JournalProceedings of the IEEE Conference on Decision and Control
    Publication statusPublished - 1989 Dec 1
    EventProceedings of the 28th IEEE Conference on Decision and Control. Part 2 (of 3) - Tampa, FL, USA
    Duration: 1989 Dec 131989 Dec 15

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Modelling and Simulation
    • Control and Optimization


    Dive into the research topics of 'Dynamic force sensing for high-speed robot manipulation using Kalman filtering techniques'. Together they form a unique fingerprint.

    Cite this