<title>Preferable movement of a multijoint robot arm using a genetic algorithm</title>

A genetic algorithm for optimizing vector-based paths of industrial manipulators

“…In the last twenty years, many developments have been made for the use of GA for robotic applications like trajectory planning for mobile robots [7] and manipulators [8], [9], [10], inverse kinematics [11], and scheduling [12]. Some of the most important contributions have been developed for trajectory planning in order to find optimal solutions for the trajectory of the manipulators.…”

“…A GA is used to determine the parameters of a polynomial to minimize the fitness of the objective function that represents the trajectory of the manipulator. An application for a two-joint arm is described in [9], where the movement and position of its endeffector is determined using a GA. With this solution, minimal joint rotation and smooth trajectories were obtained. Finally, in [10], a GA was proposed to define the trajectory at joint-space but at Cartesian space, as it is the work proposed in this paper.…”

Optimal Trajectory Planning for Design of a Crawling Gait in a Robot Using Genetic Algorithm

“…(7), (8), and (9) into Eq. (10) we will have: 12 13 1 2 12 23 2 13 23 3 2 1 12 13 2 2 12 23 2 2 13 23 3 1 2 3 14 9 3 6 8 3 6 3 3 2 0 9 3 9 0 3 6 3 3 0 5 cos 3 cos 2 cos…”

An effective robot trajectory planning method using a genetic algorithm

“…While there are numerous approaches to solving the trajectory generation problem [7][8][9][10], however, some require large computational effort, and may not result in a smooth trajectory.…”

“…Yano and Tooda [7] applied a genetic algorithm to solve the position and movement of an end-effector on the tip of a two-joint robot arm. He defined objective functions in both Cartesian space and joint space, and combined them to optimize the robot trajectory.…”