Industry Solutions:
Robotic Experience Network (Genesis Net)
Accelerating robotic evolution across industries through high-fidelity simulation and shared synthetic experience.
Humanoid & Embodied AI
Dexterous hand manipulation and bipedal gait control algorithm tuning is extremely time-consuming, and real hardware is easily damaged. Every joint parameter adjustment requires expensive physical testing cycles.
Train joint torque control in Isaac Lab-grade massively parallel simulation, achieving smooth Sim-to-Real deployment through Domain Randomization.
Logistics & Manufacturing
Minor production line layout changes or new product categories require complete robot reprogramming. Traditional approaches halt operations for days per update at extreme cost.
Auto-generate virtual replicas of new working conditions, complete tens of thousands of simulated grasping trainings overnight in the cloud, and deploy seamlessly the next day.
Service Robots
Dynamic crowds in malls and hospitals cause rule-based algorithms to deadlock. Robot performance degrades severely in extremely congested scenarios.
Through adversarial task generation, train robots for dynamic obstacle avoidance in extreme crowd conditions, covering edge cases that rule-based algorithms cannot enumerate.
Genesis Net
Service that enables cross-platform experience sharing at scale. A single robot's learned avoidance policy propagates to thousands across environments, accelerating the collective intelligence of all connected machines.
- doneFederated Learning Architecture
- doneCross-Morphology Transfer
- doneContinuous Synthetic Integration