| Literature DB >> 33501021 |
David Navarro-Alarcon1, Omar Zahra1, Christian Trejo1,2, Ernesto Olguín-Díaz2, Vicente Parra-Vega2.
Abstract
This paper presents a method for computing sensorimotor maps of braided continuum robots driven by pneumatic actuators. The method automatically creates a lattice-like representation of the sensorimotor map that preserves the topology of the input space by arranging its nodes into clusters of related data. Deformation trajectories can be simply represented with adjacent nodes whose values smoothly change along the lattice curve; this facilitates the computation of controls and the prediction of deformations in systems with unknown mechanical properties. The proposed model has an adaptive structure that can recalibrate to cope with changes in the mechanism or actuators. An experimental study with a robotic prototype is conducted to validate the proposed method.Entities:
Keywords: adaptive systems; continuum robots; neural networks; self-organizing maps; sensorimotor models
Year: 2019 PMID: 33501021 PMCID: PMC7805695 DOI: 10.3389/frobt.2019.00004
Source DB: PubMed Journal: Front Robot AI ISSN: 2296-9144