Vergleich von Algorithmen zur Bewegungsplanung für einen Robotergreifarm mit 6 Freiheitsgraden in einer Simulation

A comparative study of three motion‑planning algorithms—PRM, CHOMP, and the convex‑set‑based GCS—was conducted for a six‑degree‑of‑freedom robotic manipulator in simulated environments. The algorithms were integrated into the ROS 2/MoveIt 2 framework and benchmarked in scenarios such as a table, a narrow passage, and a bookshelf, revealing that GCS can achieve rapid planning when correctly configured, while PRM is asymptotically optimal but computationally heavy and CHOMP provides fast local refinement. The results highlight trade‑offs between optimality, computation time, and robustness for robotic arm trajectory planning.