Dexterous hands, with multiple fingers, can manipulate objects in complex ways, but they are harder to control and study than simple two-finger grippers. Most robot simulation avoid dexterous hands, making it difficult to compare performance across different hand designs.
DexSuite provides a standardized simulation environment built on the Genesis simulator. It includes 30 tasks, over 100 robot configurations, and a benchmark of 16 specific task-and-hand combinations. Researchers can teleoperate hands, collect demonstrations, and test learning algorithms in the same framework.
Tests show that dexterous hands match or beat gripper performance on many tasks, but struggle with tasks requiring precise tool use and sequential object handling. This helps focus research on where dexterous hands still need improvement, and the open-source release allows others to build on these findings.