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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

An important prerequisite for the reliability and robustness of a servicerobot is ensuring the robot's correct behavior when it performs various tasksof interest. Extensive testing is one established approach for ensuringbehavioural correctness; this becomes even more important with the integrationof learning-based methods into robot software architectures, as there are oftenno theoretical guarantees about the performance of such methods in varyingscenarios. In this paper, we aim towards evaluating the correctness of robotbehaviors in tabletop manipulation through automatic generation of simulatedtest scenarios in which a robot assesses its performance using property-basedtesting. In particular, key properties of interest for various robot actionsare encoded in an action ontology and are then verified and validated within asimulated environment. We evaluate our framework with a Toyota Human SupportRobot (HSR) which is tested in a Gazebo simulation. We show that our frameworkcan correctly and consistently identify various failed actions in a variety ofrandomised tabletop manipulation scenarios, in addition to providing deeperinsights into the type and location of failures for each designed property.

Property-Based Testing in Simulation for Verifying Robot Action Execution in Tabletop Manipulation