Bidirectional recurrent learning of inverse dynamic models for robots with elastic joints: a real-time real-world implementation.

ABSTRACT: Collaborative robots, or cobots, are designed to work alongside humans and to alleviate their physical burdens, such as lifting heavy objects or performing tedious tasks. Ensuring the safety of human-robot interaction (HRI) is paramount for effective collaboration. To achieve this, it is essential to have a reliable dynamic model of the cobot that enables the implementation of torque control strategies. These strategies aim to achieve accurate motion while minimizing the amount of torque exerted by the robot. However, modeling the complex non-linear dynamics of cobots with elastic actuators poses a challenge for traditional analytical modeling techniques. Instead, cobot dynamic modeling needs to be learned through data-driven approaches, rather than analytical equation-driven modeling. In

SUBMITTER: Valencia-Vidal B 

PROVIDER: S-EPMC10311998 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature