Optimal Trajectory Planning and Obstacle Avoidance of a Manipulator in the Presence of Ellipsoidal Obstacles Using Genetic Algorithms

In this paper, an optimal trajectory planning method is presented for robot manipulators with multiple degrees of freedom in 3D space using a new analytical technique for collision avoidance in the presence of ellipsoidal obstacles. To generate the robot’s trajectory, a genetic algorithm with a fuzzy mutation rate is introduced to have a quick access to optimal solutions in a complex workspace. A cubic spline interpolation polynomial is applied to approximate trajectories in the joint space. In order to optimize the objective function, the genetic algorithm determines a number of interior points for curve fitting using interpolation polynomials. The performance of the proposed technique is demonstrated by simulations.

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