Abstract
Motion planning of a robotic arm has been an important area of research for the last decade with the growing application of robot arms in medical science and industries. In this paper the problem of motion planning has been dealt with in two stages, first by developing appropriate cost functions to determine a set of via points and then fitting an optimal energy trajectory. Lbest Particle Swarm Optimization has been used to solve the minimization problem and its relative performance with respect to two other popular evolutionary algorithms, Differential Evolution and Invasive Weed Optimization, has been studied. Experiments indicate swarm intelligence techniques to be far more efficient to solve the optimization problem.
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Chakraborti, T., Sengupta, A., Konar, A., Janarthanan, R. (2011). Application of Swarm Intelligence to a Two-Fold Optimization Scheme for Trajectory Planning of a Robot Arm. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27242-4_11
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DOI: https://doi.org/10.1007/978-3-642-27242-4_11
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