Nvidia · NVIDIA Blog
Deformable Cluster Manipulation introduces a framework that tackles a parallel challenge: enabling systems to grasp not one object
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The framework was motivated by a real-world task: clearing a mass of tree branches that have grown over a power line, where there’s no single clean object to grab.
Key facts
- SPARR improves success rates by 38% and reduces cycle time by around 30% compared with zero-shot sim-to-real baselines
- Robotics teams from universities such as Carnegie Mellon University (CMU), ETH Zurich, MIT and University of Texas at Austin are tapping NVIDIA technologies to move physical AI research
- To build the policy, the researchers generated 2 million simulated trajectories across 8,000 objects using annotations from the GraspGen dataset and motion planning data from cuRobo
- After training on both successful and failed trajectories, Grasp-MPC learned to grasp novel objects in cluttered tabletops and shelves, achieving around 75% overall success on real robots, compared
Summary
Robotics is entering a new phase: moving from controlled demos and scripted automation toward generalizable, reliable embodied autonomy in the real world. At the International Conference on Robotics and Automation (ICRA), eight of NVIDIA Research’s 28 accepted papers show how simulation-to-real transfer is becoming a foundation for that shift, helping robots perceive, reason, plan and act across dynamic, unpredictable environments. Together, the papers span the full stack of challenges robot developers face: coordinating multiple arms in parallel, building policies that generalize across robot bodies, grasping novel objects in clutter, performing precise assembly and developing vision-language-action models that reason before they move. The throughline is clear: sim-to-real is becoming a foundation for robots that can adapt, generalize, and operate with greater reliability outside the lab. Picture a pharmaceutical lab run by robotic arms: picking up tubes, transferring liquids, mixing reagents, each step taking different amounts of time, all requiring careful coordination.