Benchmarking motion planners available in Moveit!

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At Shadow Robot, we use the Universal Robot Arms (UR5 and UR10) with our robot hands to perform experiments in order to improve our robot manipulation capabilities. However, a challenge remains to find accurate and reliable plans to move the arm around our environments even for simple movements. In several cases, the planner algorithms failed to find a plan in a reasonable amount of time or the plan generated makes the robot perform unnecessary movements that might be dangerous to execute for the real arm.

Motion planning is a common problem in robotics and even for the simple problem of finding a path connecting two states while avoiding collisions, there is no efficient solution for the general case. This inspired us to provide the tools to perform rigorous testing of the different planners available and to provide researchers tools to help them find solutions for their specific problems. We use the well-know motion planning framework MoveIt!, that itself does not provide motion planning, but instead is designed to work with planners or planning libraries.

Within MoveIt!, we used the MoveIt! ROS Benchmarks package which provides methods to benchmark motion planning algorithms and aggregate/plot statistics using the OMPL Planner Arena. Here you can follow an example in which they demonstrate how the benchmarking can be run for a Fanuc M-10iA.

We have proposed a series of benchmark problems that are designed to exercise the planners in different scenarios focused specially on common manipulation problems. Different set of queries were defined in each scenario with difficult levels of difficulty with the intention of testing the performance of the planners. Additionally a set of valid random queries were generated in each scenario to validate the results of each planner.

These sets of benchmark problems intend to help the community as a stating point and we encurage researchers to contribute with more scenes and queries that exercise other capabilities of planners.