Trajectory Planning For Six Degree-of-freedom Manipulator Based On Immune Multi-objective

Trajectory planning is one of the fundamental issues in designing and controlling for robot manipulators. In order to optimize the performance of manipulator and improve its efficiency, this paper takes execution time and energy consumption as the optimization objectives during the motion., we use immune multi-objective algorithm to optimize the manipulator’s trajectory which has been given path and constraints, and a new constraint handling strategy is designed in this paper. Finally, we utilize non-uniform rational B-spline to fit a given path composed of a set of discrete position dots, which guarantee sthe manipulator on its original path, and also achieves the desired performance. Firstly, we make reviews about the current research of artificial multi-objective optimization algorithms and trajectory planning of manipulators based on single-objective and multi-objective method respectively. And on this basis, we propose to use the improved immune multi-objective algorithm to optimize the trajectory of six-degree-of-freedom manipulator. Secondly, some basic knowledge of manipulators is introduced, such as the basic components and the relevant technical parameters of manipalator system,, the kinematics and inverse kinematics involved in manipulator controlling.Then the details of six-degree-of-freedom manipulator are introduced in this paper. And then weadopt an improved D-H method to establish a comparetively simple manipulator’s mathematical model.through analysis and simulation, the validity and feasibility of new model are verified.The feasibility of our proposed model are verified through concrete analysis and simulation. Thirdly, the basic principle of manipulator’s trajectory planning is elaborated. We make a presentation focused on trajectory planning and generating in joint space. Considering the manipulator’s constraint, we propose a new constrained immune multi-objective optimization algorithm, namely CIMOA. It employs a new strategy to handle constraints, which means that it systematically takes the convegence, uniformity and feasibility of solution as a sub-problem in a multi-objective. Numerical tests show that the solutions generated by this method not only enjoy good feasibility and diversity, but also close to the real Pareto front.Finally, a model of trajectory planning for six-DOF manipulator based on immune multi-objective is established. Given path and system constraints, the CIMOA algorithm is applied in trajectory planning to achieveminimum execution time and minimum energy over manipulator motion.. Non-uniform rational B-splines have the advantages of local support and modify. We use high-degree NURBS to construct the trajectory curves in joint space, which ensures the high-degree continuity and smoothness of joint speed, acceleration and jerk. We let the manipulator do transferring task on hardware platform to obtain the desiredparameters, and then the optimization results is simulated on Matlab.Experimental results demostrate that the total executing time of manipulator is significantly shorter and the consuming energy is lower than before, the trajectory in joint space is also smooth. Therefore,we optimize the trajectory planning for six-DOF manipulator based on immune multi-objective.