English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

When robots are able to see and respond to their surroundings, a whole newworld of possibilities opens up. To bring these possibilities to life, therobotics industry is increasingly adopting camera-based vision systems,especially when a robotic system needs to interact with a dynamic environmentor moving target. However, this kind of vision system is known to have low datatransmission rates, packet loss during communication and noisy measurements asmajor disadvantages. These problems can perturb the control performance and thequality of the robot-environment interaction. To improve the quality of visualinformation, in this paper, we propose to model the dynamics of the motion of atarget object and use this model to implement an Extended Kalman Filter basedon Intermittent Observations of the vision system. The effectiveness of theproposed approach was tested through experiments with a robotic arm, a cameradevice in an eye-to-hand configuration, and an oscillating suspended block as atarget to follow.

Tracking and Following a Suspended Moving Object using Camera-Based Vision System