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

We present a novel approach to perform probabilistic collision detectionbetween a high-DOF robot and high-DOF obstacles in dynamic, uncertainenvironments. In dynamic environments with a high-DOF robot and movingobstacles, our approach efficiently computes accurate collision probabilitybetween the robot and obstacles with upper error bounds. Furthermore, wedescribe a prediction algorithm for future obstacle position and motion thataccounts for both spatial and temporal uncertainties. We present a trajectoryoptimization algorithm for high-DOF robots in dynamic, uncertain environmentsbased on probabilistic collision detection. We highlight motion planningperformance in challenging scenarios with robot arms operating in environmentswith dynamically moving human obstacles.

Fast and Bounded Probabilistic Collision Detection in Dynamic Environments for High-DOF Trajectory Planning