In this work, modular reconfigurable robots are studied, with emphasis on manipulators and space application. A basis for motion planning and manipulation planning is established, which is the focus of this thesis. From this, a suitable approach for a motion planner is then chosen and implemented. The developed motion planner should be able to adapt to reconfigurations of the robot, which are imposed on the manipulation planner. The planner then enables the robot to execute tasks safely. The position and orientation of all obstacles and robot modules are assumed as given. The environment, which the obstacles are part of, is assumed as static. A kinematic chain is built, so the planner can compute the tool-pose for a given set of joint-positions. The planner itself is based on RRT and tries to extend from known configurations to a given goal pose. By numerical determination of the local Jacobian, the planner can guess intelligently how to move the joints. During this work, the planner is implemented almost from scratch. All mathematical concepts needed for the implementation are therefore introduced before the actual implementation is explained. In the end, the algorithm is demonstrated to be viable for robots with 6, 7 or 8 degrees of freedom in different environments. Three ways of parallelizing the planning process are shown and analyzed with respect to their suitability and expected runtime on distributed hardware.