NVIDIA researchers showed robots trained in simulation can now perform more reliably in real-world tasks.
Grasp-MPC adjusts robotic grasps in real time, refining motion as the robot approaches an object instead of following a fixed plan. Robots trained entirely in simulation are beginning to perform more reliably in the real world, according to a series of new robotics research papers presented by NVIDIA at the International Conference on Robotics and Automation .
The studies focus on one of robotics’ biggest challenges: narrowing the “sim-to-real” gap, where machines trained in virtual environments struggle when deployed outside controlled lab conditions. NVIDIA Research said eight of its accepted ICRA papers demonstrated advances in robotic navigation, grasping, assembly, and reasoning using simulation-based learning systems. The projects aim to help robots adapt to unpredictable real-world environments instead of relying on rigid scripted behaviors.
The work spans several areas of robotics, including multi-arm coordination, humanoid navigation, object manipulation, and vision-language-action models that allow robots to reason through tasks before acting. One of the highlighted systems, called COMPASS, trains robots entirely inside NVIDIA Isaac Lab simulations before transferring those skills to different physical robot bodies.
Researchers said the framework achieved about 80 percent success across 20 real-world navigation trials involving autonomous mobile robots and humanoids, while improving average success rates by 4.5 times compared with imitation-learning baselines. Another project, Grasp-MPC, focused on robotic grasping in cluttered environments. Instead of relying on a fixed movement plan, the system continuously adjusts its motion while approaching objects. The researchers trained the model using two million simulated trajectories involving 8,000 objects.
In real-world testing, the system achieved about 75 percent grasp success on unfamiliar objects, compared with 41 percent using baseline methods. NVIDIA researchers also developed a system called Deformable Cluster Manipulation designed for handling tangled or flexible materials such as tree branches around power lines. The framework trains robots to use their entire arm instead of just a gripper, allowing machines to gather or sweep aside clusters of objects in ways that resemble human movement.
Several papers also focused on improving robotic assembly and reasoning capabilities. Researchers said the method improved assembly success rates by 38 percent and reduced cycle time by around 30 percent compared with zero-shot sim-to-real baselines.ignore irrelevant visual clutter while focusing only on objects needed to complete a task. NVIDIA said the framework improved real-world robotic accuracy by as much as 41 times for policies trained purely in simulation.
A separate collaboration involving Carnegie Mellon University, the University of Utah, and the University of Sydney introduced SEAL, a framework designed to prevent robots from carrying out actions that differ from their planned reasoning steps.said its broader robotics ecosystem continues expanding through open datasets and simulation platforms including Isaac Lab, Isaac GR00T X Embodiment Sim, and Omniverse NuRec. With over a decade-long career in journalism, Neetika Walter has worked with The Economic Times, ANI, and Hindustan Times, covering politics, business, technology, and the clean energy sector.
Passionate about contemporary culture, books, poetry, and storytelling, she brings depth and insight to her writing. When she isn’t chasing stories, she’s likely lost in a book or enjoying the company of her dogs. AI and Robotics
Humanoid Robots Isaac Lab Nvidia Robot Navigation Robotics Sim-To-Real Simulation Training
United States Latest News, United States Headlines
Similar News:You can also read news stories similar to this one that we have collected from other news sources.
Nvidia CEO Begs Execs to Stop Telling Workers They're Fired Because of AINvidia CEO Jensen Huang accused other executives of wrongly justifying layoffs on AI — and telling them to cut it out.
Read more »
NVIDIA-powered supercomputer aims to bring smart computing into orbitNew rugged supercomputer using NVIDIA IGX Thor aims to bring faster computing into orbit
Read more »
Kevin O'Leary & Nvidia's Co-Founder Among Recipients Of AI HonorsThey will be among the honorees at next week's awards, sponsored by the Washington AI Network.
Read more »
Nvidia’s Jensen Huang joins advisory board of China’s prestigious Tsinghua University: reportOutgoing Apple CEO Tim Cook serves as chairman of the advisory board, members of which also include SpaceX boss Elon Musk, Meta chief Mark Zuckerberg, Microsoft’s Satya Nadella and JPMorgan CEO Jam…
Read more »