A method for collision-free motion planning of a first manipulator with closed kinematics, comprising: - Defining a dynamic optimization problem, - Solving the optimization problem via a numerical approach, and - Determining a first movement path for the first manipulator based on the solution of the optimization problem, - Executing the first movement path, wherein the dynamic optimization problem comprises a cost function which weights states and control variables of the first manipulator, a dynamic which defines states and control variables of the first manipulator as a function of time, at least one inequality constraint for a distance to collisions, and at least one equality constraint for closed kinematics, characterized in that solving the optimization problem is carried out successively and in parallel to the execution of the first movement path by including an end time representing the duration of the movement in the dynamic optimization problem, and the numerical approach determines in a first time step a trajectory from a start point (q s) to a target point (q G), executes in a second time step a beginning of this trajectory up to an intermediate point (q 1), and optimizes at the same time the movement from the intermediate point (q 1) to the target point (q G) based on an adjusted optimization problem that corresponds to the dynamic optimization problem and which considers a state at an end of the first time step as initial condition, wherein this stepwise procedure is repeated until the target point (q G) is reached within a time step by including a final constraint for the end time in the optimization problem, and wherein the numerical approach shortens, starting from an initial estimate for the end time, the end time after each time step until the target point (q G) is reached exactly within a last time step. - Defining a dynamic optimization problem, - Solving the optimization problem via a numerical approach, and - Determining a first movement path for the first manipulator based on the solution of the optimization problem, - Executing the first movement path, wherein the dynamic optimization problem comprises a cost function which weights states and control variables of the first manipulator, a dynamic which defines states and control variables of the first manipulator as a function of time, at least one inequality constraint for a distance to collisions, and at least one equality constraint for closed kinematics, characterized in that solving the optimization problem is carried out successively and in parallel to the execution of the first movement path by including an end time representing the duration of the movement in the dynamic optimization problem, and the numerical approach determines in a first time step a trajectory from a start point (q s) to a target point (q G), executes in a second time step a beginning of this trajectory up to an intermediate point (q 1), and optimizes at the same time the movement from the intermediate point (q 1) to the target point (q G) based on an adjusted optimization problem that corresponds to the dynamic optimization problem and which considers a state at an end of the first time step as initial condition, wherein this stepwise procedure is repeated until the target point (q G) is reached within a time step by including a final constraint for the end time in the optimization problem, and wherein the numerical approach shortens, starting from an initial estimate for the end time, the end time after each time step until the target point (q G) is reached exactly within a last time step. wherein the dynamic optimization problem comprises a cost function which weights states and control variables of the first manipulator, a dynamic which defines states and control variables of the first manipulator as a function of time, at least one inequality constraint for a distance to collisions, and at least one equality constraint for closed kinematics, characterized in that solving the optimization problem is carried out successively and in parallel to the execution of the first movement path by including an end time representing the duration of the movement in the dynamic optimization problem, and the numerical approach determines in a first time step a trajectory from a start point (q s) to a target point (q G), executes in a second time step a beginning of this trajectory up to an intermediate point (q 1), and optimizes at the same time the movement from the intermediate point (q 1) to the target point (q G) based on an adjusted optimization problem that corresponds to the dynamic optimization problem and which considers a state at an end of the first time step as initial condition, wherein this stepwise procedure is repeated until the target point (q G) is reached within a time step by including a final constraint for the end time in the optimization problem, and wherein the numerical approach shortens, starting from an initial estimate for the end time, the end time after each time step until the target point (q G) is reached exactly within a last time step.