This paper presents an evolutionary approach to the Inverse Kinematics problem. The Inverse Kinematics problem concerns finding the placement of a manipulator that satisfies certain conditions. In this paper apart from reaching the target point the manipulator is required to avoid a number of obstacles. The problem which we tackle is dynamic: the obstacles and the target point may be moving which necessitates the continuous update of the solution. The evolutionary algorithm used for this task is a modification of the Infeasibility Driven Evolutionary Algorithm (IDEA) augmented with a prediction mechanism based on the ARIMA model. © 2012 Springer-Verlag.
CITATION STYLE
Filipiak, P., Michalak, K., & Lipinski, P. (2012). A predictive evolutionary algorithm for dynamic constrained inverse kinematics problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7208 LNAI, pp. 610–621). https://doi.org/10.1007/978-3-642-28942-2_55
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