Motion planning, and in particular in tight settings, is a key problem in robotics and manufacturing. One infamous example for a difficult, tight motion planning problem is the Alpha Puzzle. Many works deal with motion planning in tight scenarios and demonstrate solutions for the Alpha Puzzle in simulation. However, we have not yet seen a real-life robotic arm solving the puzzle in the physical world. The transition from simulation to a real-world solution requires dealing with various difficulties beyond the geometry of the problem, including finding a suitable grasp and robot placement, accounting for model inaccuracies, avoiding robot singularities and more. We present a first demonstration in the real world of an Alpha Puzzle solution with a Universal Robotics UR5e, using a solution path generated from our previous work. After manually placing the robot next to the puzzle pieces, the entire process is automatically planned and executed given the solution path and the robot’s placement.
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