Trajectory planning using Mixed Reality: an experimental validation
Marco Piccinelli, Andrea Gagliardo, Umberto Castellani, Riccardo Muradore · 2021 20th International Conference on Advanced Robotics (ICAR) · 2021
Trajectory planning is at the very core of robotics. Nonetheless, it is not trivial to plan trajectories for industrial or cooperative robots in an intuitive way by non roboticists. Visualizing in 3D a trajectory consisting of a sequence of positions of the end-effector and its orientations is difficult, and becomes even more challenging when kinematics and dynamics constraints should be taken into account. In this work we propose a novel approach, exploiting Mixed Reality, to improve and make easier the planning phase by allowing the user to 'dropping’ way points and leaving to the system the computation of the trajectory, its visualization in augmented reality and, finally, send it to the real robot controller. The method has been experimentally validated on a Panda robot by Franka Emika.