Rapidly-exploring random trees (RRT) and their variant are a very power solution for solving motion planning problem in robotics, but they suffer from finding an optimise solution and the generated path is usually jerky with redundant movements. Sample based-optimisation-based planners benefit the robustness of RRT and the possibility of imposing a cost function. Here in this work, I
Operating a handwheel with two schunk LWA 4D manipulators. Corresponding paper in IROS 2015.
In this task, an orientation constraint has been imposed to the planner such that the orientation of end effector is fixed during the task. The planner checks the self-collision and collision between robot and the environment. Corresponding paper in IROS 2015.