Dynamics and path tracking of continuum robotic arms using data-driven identification tools

Autor:	Aida Parvaresh, S. Ali A. Moosavian
Rok vydání:	2021
Předmět:	Identification (information) Control and Systems Engineering Control theory Computer science Continuum (topology) General Mathematics Path tracking Dynamics (mechanics) Robotic arm Software Computer Science Applications Data-driven
Zdroj:	Robotica. 40:1098-1124
ISSN:	1469-8668 0263-5747
DOI:	10.1017/s026357472100093x
Popis:	In this paper, forward/inverse dynamics of a continuum robotic arm is developed using a data-driven approach, which could tackle uncertainties and extreme nonlinearities to obtain reliable solutions. By establishing a direct mapping between the actuator and task spaces, the unnecessary mappings of actuator-to-configuration then configuration-to-task are eliminated, to reduce extra computational cost. The proposed approach is validated through simulation (based on Cosserat rod theory) and experimental tests on RoboArm. Next, path tracking in the presence/absence of obstacles as well as load carrying maneuver are investigated. Finally, the obtained results concerning repeatability, scalability, and disturbance rejection performance of the approach are discussed.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::395a067d35ffad7025bb81c537df470a https://doi.org/10.1017/s026357472100093x Zobrazit plný text záznamu