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

A typical approach to creating complex robot behaviors is to compose atomiccontrollers, or skills, such that the resulting behavior satisfies a high-leveltask; however, when a task cannot be accomplished with a given set of skills,it is difficult to know how to modify the skills to make the task possible. Wepresent a method for combining symbolic repair with physicalfeasibility-checking and implementation to automatically modify existing skillssuch that the robot can execute a previously infeasible task.  We encode robot skills in Linear Temporal Logic (LTL) formulas that captureboth safety constraints and goals for reactive tasks. Furthermore, our encodingcaptures the full skill execution, as opposed to prior work where only thestate of the world before and after the skill is executed are considered. Ourrepair algorithm suggests symbolic modifications, then attempts to physicallyimplement the suggestions by modifying the original skills subject to LTLconstraints derived from the symbolic repair. If skills are not physicallypossible, we automatically provide additional constraints for the symbolicrepair. We demonstrate our approach with a Baxter and a Clearpath Jackal.

Physically-Feasible Repair of Reactive, Linear Temporal Logic-based, High-Level Tasks