Analysis of grasping failures in multi-rigid body simulations

Abstract

Rigid body simulation libraries are sophisticated software systems that include multiple, tricky to implement numerical algorithms: solving initial value problems, root finding, geometric intersection (collision detection) and contact determination, and solving mathematical programming and optimization problems. How and why such systems fail to produce expected behavior is not readily known and not easy to discern; few of the components described above use reference implementations or are modular, for example, which makes attempting to identify points of failure challenging. Additionally, most libraries present an extraordinary number of parameters to be tuned, which complicates assessment. For the field of robotics, such failures are frustrating. One of the most seminal tasks in the domain, grasping of rigid objects, can require considerable parameter tuning. This paper uses a recent development, the support of four open-source physics engines in the GAZEBO simulator, to assess the ability of simulated robots to maintain grasps of rigid objects. We develop a metric that captures grasping performance and run a multitude of experiments to ascertain causes of failure. We have made all of our experimental code and data freely available, which allows others to reproduce our results and the authors of the corresponding physics engines to compete toward maximizing performance on the grasping task.