Loading...

Use of PSO in parameter estimation of robot dynamics; part one: No need for parameterization

Jahandideh, H ; Sharif University of Technology | 2012

964 Viewed
  1. Type of Document: Article
  2. Publisher: 2012
  3. Abstract:
  4. 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
  5. Keywords:
  6. Inverse dynamic model ; Robust least squares ; Off-line approaches ; Offline ; Parameterized ; Robot dynamics ; Robust analytical methods ; Simulated experiments ; Swarm Intelligence ; Least Square ; Robot parameters ; Estimating parameters ; Simulated system ; Total least squares ; Artificial intelligence ; Dynamics ; Parameter estimation ; Particle swarm optimization (PSO) ; Robots ; System theory ; Robustness (control systems) ; Parameterization ; Robots
  7. Source: 2012 16th International Conference on System Theory, Control and Computing, ICSTCC 2012 - Joint Conference Proceedings ; 2012 ; 9786068348483 (ISBN)
  8. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6379290&filter=AND%28p_Publication_Number:6365889%29