KUKA smart pick-and-place in Isaac Sim
Perception-driven grasps, multiple end effectors, and orientation-aware placement.
Problem
Industrial pick-and-place must handle varied part poses, gripper limits, and station constraints. Teams need a simulation sandbox to iterate grasp strategies, tooling, and vision before shop-floor integration and production sign-off.
Solution
We simulated a KUKA-class industrial manipulator in NVIDIA Isaac Sim and Omniverse with multiple end effectors, grasp sampling, and vision-driven selection of pick and place poses including orientation-aware placement for stable stacking and handoff.
Outcome
The simulation demonstrates detection-driven, adaptive pick-and-place with an industrial arm de-risking camera calibration, grasp policies, and station IO before hardware cutover.
Technologies
Gallery
Project Media