While cooperation among robots enhances the capabilities of the robotic systems and their applications, it imposes kinematic, dynamic, and control complications on them due to the closed chains created. In this study, the kinematic, dynamic, and control aspects of a set of planar cooperative manipulators are initially investigated to be followed by a study of the optimal path planning (using different optimization indexes) for the two independent phases of approaching to and transferring an object by manipulators. The mechanism’s dynamic equations for the approaching phase will be derived using the Recursive Newton-Euler and the Langrage methods while the method of Lagrange Approach for Constrained Systems will be employed to derive those for the transferring phase. In continuation, various methods of robotic control are introduced to design two controllers based on computed torque and fuzzy methods and the problem of locating the mechanism on the desired path by these two controllers is investigated. The main objective of the present study is optimal path planning. As already said above, the problem is investigated for the two phases of a set of cooperating manipulator approaching to and transferring an object, in both the joint and work spaces of the robot, respectively. In the approaching phase, optimization is based on the three indexes, time (to minimize the time that the manipulator approaches the object), kinematics (to minimize the squared second norm of the joint velocity along the trajectory), and dynamics (to minimize manipulators' energy consumption). In the transferring phase, the kinematic and dynamic indexes are also optimized to achieve an optimized trajectory. The dynamic optimization problem is reformulated as a parametric or static optimization problem using approximation equations and two different methods of physical discretization, mathematical discretization. In the mathematical discritization two approaches are implemented using simple polynomials of the time function, and mathematical discretization using a linear combination of a finite number of shifted Legendre polynomials. These equations are then solved using GA. Three sets of kinematic, dynamic, and geometrical constraints are effected as penalty functions on the system and it is found that the mathematical discretization using a linear combination of a finite number of shifted Legendre polynomials leads to obtaining the global optimum point for the three indexes considered due to its extensive search limit. Keywords: Cooperative Manipulator, Optimal Trajectory Planning, Dynamic Optimization, GA