2012/11/06 by Hossein Jahandideh, Jahandideh, Hossein, Mehrzad Namvar +1
Computer Science · Engineering · #Adaptive Control of Nonlinear Systems #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Robot Manipulation and Learning #Robotic Mechanisms and Dynamics #Robotic Path Planning Algorithms #Robotics (cs.RO) #cs.RO
paper · pdf · doi:10.48550/arxiv.1211.1339
6 pages, 7 tables, 3 figures published in the International Conference on System Theory, Control and Computing 2012 (IEEE) conference proceedings, to be indexed in IEEEXplore
arxiv created 2012/11/06 · openalex publication_date 2012/11/06 · arxiv updated 2012/11/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Offline procedures for estimating parameters of robot dynamics are practically based on the parameterized inverse dynamic model. In this paper, we present a novel approach to parameter estimation of robot dynamics which removes the necessity of parameterization (i.e. finding the minimum number of parameters from which the dynamics can be calculated through a linear model with respect to these parameters). This offline approach is based on a simple and powerful swarm intelligence tool: the particle swarm optimization (PSO). In this paper, we discuss and validate the method through simulated experiments. In Part Two we analyze our method in terms of robustness and compare it to robust analytical methods of estimation.