Reproduce “GraspBench: Execution-Aware Cross-Robot Evaluation of 6-DoF Grasp Generation in MuJoCo” on OpenResearch
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About this paper
Abdul Basit, Bibek Poudel, Muhammad Shafique
GraspBench evaluates grasp generators by filtering proposals for robot-specific feasibility, planning motion, and running a fixed simulated approach-close-lift trial. It records lift success across 540 intended scenarios per method. GraspGen succeeds in 395/540 (73.1%), versus EconomicGrasp’s 343/540 (63.5%), a paired advantage of 9.6 percentage points (95% interval 0.9–19.6). These are configured-pipeline results on this fixed grid, not intrinsic model rankings or evidence of real-world transfer.
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