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

Dynamic Movement Primitives (DMPs) offer great versatility for encoding,generating and adapting complex end-effector trajectories. DMPs are also verywell suited to learning manipulation skills from human demonstration. However,the reactive nature of DMPs restricts their applicability for tool use andobject manipulation tasks involving non-holonomic constraints, such as scalpelcutting or catheter steering. In this work, we extend the Cartesian space DMPformulation by adding a coupling term that enforces a pre-defined set ofnon-holonomic constraints. We obtain the closed-form expression for theconstraint forcing term using the Udwadia-Kalaba method. This approach offers aclean and practical solution for guaranteed constraint satisfaction atrun-time. Further, the proposed analytical form of the constraint forcing termenables efficient trajectory optimization subject to constraints. Wedemonstrate the usefulness of this approach by showing how we can learn roboticcutting skills from human demonstration.

Learning robotic cutting from demonstration: Non-holonomic DMPs using the Udwadia-Kalaba method