Physical trials risked hardware damage. Simulating years of learning in hours cut dev cycles from weeks to days.
A developer of general-purpose humanoid robots designed to work in existing warehouses where installing fixed automation is too costly and slow.
Achieving reliable whole-body control requires handling unpredictable variables, from slippery floors to physical bumps from human workers....
“Isaac Sim running on NVIDIA GPUs lets us simulate years of real-world learning for Digit in just hours. That simulation speedup means we can train for all the conditions we might see on the factory floor.”
Bipedal humanoid robots for warehouse automation and material handling.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Agility Robotics's Robot training simulation is part of this use case:
Related implementations across industries and use cases
Programming robots took hundreds of hours. Using digital twins, engineers now train precise tasks in half a day.
Potholes and pedestrians taxed legacy compute. A 5x boost in video processing power now enables 12-hour autonomous delivery shifts.
Videos obsolete in 30 days forced expert re-shoots. Now, AI generates training from text, cutting production from days to hours.
Programming robots took hundreds of hours. Using digital twins, engineers now train precise tasks in half a day.
Potholes and pedestrians taxed legacy compute. A 5x boost in video processing power now enables 12-hour autonomous delivery shifts.
Manual 12-day checks for EU deforestation rules created risk. Now, an AI traces the supply chain in 3 minutes, ensuring full compliance.
Minor updates required 3.5-hour re-recordings. Now, teams use AI avatars to regenerate training videos from slides in 30 minutes.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.
Physical trials risked hardware damage. Simulating years of learning in hours cut dev cycles from weeks to days.
A developer of general-purpose humanoid robots designed to work in existing warehouses where installing fixed automation is too costly and slow.
Achieving reliable whole-body control requires handling unpredictable variables, from slippery floors to physical bumps from human workers....
“Isaac Sim running on NVIDIA GPUs lets us simulate years of real-world learning for Digit in just hours. That simulation speedup means we can train for all the conditions we might see on the factory floor.”
Bipedal humanoid robots for warehouse automation and material handling.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Agility Robotics's Robot training simulation is part of this use case:
Related implementations across industries and use cases
Programming robots took hundreds of hours. Using digital twins, engineers now train precise tasks in half a day.
Potholes and pedestrians taxed legacy compute. A 5x boost in video processing power now enables 12-hour autonomous delivery shifts.
Videos obsolete in 30 days forced expert re-shoots. Now, AI generates training from text, cutting production from days to hours.
Programming robots took hundreds of hours. Using digital twins, engineers now train precise tasks in half a day.
Potholes and pedestrians taxed legacy compute. A 5x boost in video processing power now enables 12-hour autonomous delivery shifts.
Manual 12-day checks for EU deforestation rules created risk. Now, an AI traces the supply chain in 3 minutes, ensuring full compliance.
Minor updates required 3.5-hour re-recordings. Now, teams use AI avatars to regenerate training videos from slides in 30 minutes.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.