GraspBench: Execution-Aware Cross-Robot Evaluation of 6-DoF Grasp Generation in MuJoCo
Overview
The paper presents GraspBench, a controlled evaluation framework within the MuJoCo simulator designed to assess 6-degree-of-freedom grasp generation pipelines.
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Event evidence and corrections
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Reported quantity · Reported success rate: 73.1 percent · reported trials
“on runner. GraspGen achieves the highest overall success rate (73.1%), followed by EconomicGrasp (63.5%), while robot- and object-conditioned analyses reveal substantial variation across embodiments and object geometries. GPG produces the largest native candidate sets but achieves 44.3% success, indicating that proposal volume alone does not guarantee robot-executable grasps. Cluster-aware paired intervals support th”
Exact source · revision 1Source owner not reported
Reported quantity · scenarios per method: 540 other · Basis not reported
“ring, motion planning, and fixed approach-close-lift execution. GraspBench evaluates six configured pipelines across four robot embodiments, five diagnostic objects, and a structured tabletop pose grid, yielding 540 scenarios per method and 3,240 method-scenario evaluations in total. Missing outputs are conservatively counted as failures, and success follows the binary lift criterion produced by each method's executi”
Exact source · revision 1Source owner not reported
Reported quantity · method-scenario evaluations: 3240 other · Basis not reported
“ring, motion planning, and fixed approach-close-lift execution. GraspBench evaluates six configured pipelines across four robot embodiments, five diagnostic objects, and a structured tabletop pose grid, yielding 540 scenarios per method and 3,240 method-scenario evaluations in total. Missing outputs are conservatively counted as failures, and success follows the binary lift criterion produced by each method's executi”
Exact source · revision 1Source owner not reported
Reported quantity · robot embodiments: 4 robots · Basis not reported
“ring, motion planning, and fixed approach-close-lift execution. GraspBench evaluates six configured pipelines across four robot embodiments, five diagnostic objects, and a structured tabletop pose grid, yielding 540 scenarios per method and 3,240 method-scenario evaluations in total. Missing outputs are conservatively counted as failures, and success follows the binary lift criterion produced by each method's executi”
Exact source · revision 1Source owner not reported
Reported quantity · diagnostic objects: 5 other · Basis not reported
“ring, motion planning, and fixed approach-close-lift execution. GraspBench evaluates six configured pipelines across four robot embodiments, five diagnostic objects, and a structured tabletop pose grid, yielding 540 scenarios per method and 3,240 method-scenario evaluations in total. Missing outputs are conservatively counted as failures, and success follows the binary lift criterion produced by each method's executi”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalGraspBench: Execution-Aware Cross-Robot Evaluation of 6-DoF Grasp Generation in MuJoCo
The paper presents GraspBench, a controlled evaluation framework within the MuJoCo simulator designed to assess 6-degree-of-freedom grasp generation pipelines.
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