A soft computing approach for inverse kinematics of robot manipulators. (September 2018)

• Record Type: Journal Article
• Authors: Lopez-Franco, Carlos; Hernandez-Barragan, Jesus; Alanis, Alma Y.; Arana-Daniel, Nancy
• Is Part Of: Engineering applications of artificial intelligence. Volume 74(2018)
• Page Start: 104
• Page End: 120
• Publication Date: 2018-09
• Subjects: Forward kinematics -- Inverse kinematics -- Soft computing -- Path tracking; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2018.06.001
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: The solution of the inverse kinematics problem is an essential capability for robotic manipulators. This capability is used to solve tasks such as path planning, control of manipulators, object grasping, etc. In this paper, we present an approach for solving the inverse kinematics of robot arm manipulators using a soft computing approach. Given a desired end effector pose, the proposed approach is able to solve both the position and orientation for the inverse kinematic problem. In addition, the proposed approach avoids singularities configurations, since, it is based on the forward kinematics equations. We present simulations and experiments, where a comparative study among some selected soft computing algorithms is realized. The simulations and experiments illustrate the effectiveness of the proposed approach.