Safe Execution of Learned Orientation Skills with Conic Control Barrier Functions

Zheng Shen, Matteo Saveriano, Fares J. Abu-Dakka, Sami Haddadin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the field of Learning from Demonstration (LfD), Dynamical Systems (DSs) have gained significant attention due to their ability to generate real-time motions and reach predefined targets. However, the conventional convergence-centric behavior exhibited by DSs may fall short in safety-critical tasks, specifically, those requiring precise replication of demonstrated trajectories or strict adherence to constrained regions even in the presence of perturbations or human intervention. Moreover, existing DS research often assumes demonstrations solely in Euclidean space, overlooking the crucial aspect of orientation in various applications. To alleviate these shortcomings, we present an innovative approach geared toward ensuring the safe execution of learned orientation skills within constrained regions surrounding a reference trajectory. This involves learning a stable DS on SO(3), extracting time-varying conic constraints from the variability observed in expert demonstrations, and bounding the evolution of the DS with Conic Control Barrier Function (CCBF) to fulfill the constraints. We validated our approach through extensive evaluation in simulation and showcased its effectiveness for a cutting skill in the context of assisted teleoperation.

Original languageEnglish (US)
Title of host publication2024 IEEE International Conference on Robotics and Automation, ICRA 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages13376-13382
Number of pages7
ISBN (Electronic)9798350384574
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Robotics and Automation, ICRA 2024 - Yokohama, Japan
Duration: May 13 2024May 17 2024

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2024 IEEE International Conference on Robotics and Automation, ICRA 2024
Country/TerritoryJapan
CityYokohama
Period5/13/245/17/24

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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