This study addresses a point-to-point of an arm robot motion planning in complex geometrical obstacle considering all kinematics and dynamics constraints. A continuous function of a seventh degree polynomial is utilized as a joint angle path. The path planning optimization objective is to minimize a joint angle traveling &stance under avoiding collision constraint. After the best path has been discovered, the trajectories will be optimized with an objective is to minimize the total traveling time and the torque under the maximum velocity, the maximum acceleration, the maximum jerk and the maximum torque constraints. Three Degree of Freedom (3-DOF) planar robot will be utilized to simulate the proposed method. The computational strategy utilizing a Genetic Algorithm (GA) will be presented. There is no information regarding the region of the feasible seventh degree polynomial joint angle path so that the GA should search it first. At the first computation where the population is generated randomly, all individuals commonly collide with obstacles. It needs a requirement to escape from zero fitness. After the feasible individual has been discovered, the GA should evolve this individual to find the best one with the highest fitness value. Results show that the feasible joint angle path which is very smooth in the motion has succeeded to be found. The trajectories are also hscovered successfully without exceeding the constraint values.
- Arm robot motion planning
- Genetic algorithm
- Seventh degree polynomial joint angle path