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

This paper introduces a novel approach for learning polynomialrepresentations of physical objects. Given a point cloud data set associatedwith a physical object, we solve a one-class classification problem to boundthe data points by a polynomial sublevel set while harnessing Sum-of-Squares(SOS) programming to enforce prior shape knowledge constraints. By representingobjects as polynomial sublevel sets we further show it is possible to constructa secondary SOS program to certify whether objects are packed correctly, thatis object boundaries do not overlap and are inside some container set. Whilenot employing reinforcement learning (RL) in this work, our proposed secondarySOS program does provide a potential surrogate reward function for RLalgorithms, autonomously rewarding agents that propose object rotations andtranslations that correctly pack objects within a given container set.

Learning Polynomial Representations of Physical Objects with Application to Certifying Correct Packing Configurations