Digital Twin
What is Digital Twin in Humanoid Robotics?
Virtual replica of a physical robot used for simulation, testing, and monitoring.
Enables testing software updates, training scenarios, and troubleshooting without risking real hardware or disrupting operations.
How Digital Twin Works
A digital twin is a software model that mirrors a physical robot's configuration, state, and behavior. The twin includes kinematic models (joint structure), dynamic models (mass, inertia), sensor models, and control systems. Real-time data from the physical robot (joint positions, sensor readings, operational status) synchronizes with the twin, keeping it current. Engineers use the twin to simulate "what if" scenarios - testing new control algorithms, predicting maintenance needs, or evaluating different task strategies. Machine learning models can be trained in the twin environment safely. The twin may run in parallel with the physical robot, providing a sandbox for experimentation without operational risk.
Applications in Humanoid Robots
Digital twins enable testing software updates in simulation before deploying to production robots. Fleet managers monitor robot health and predict maintenance by analyzing twin data. Training scenarios prepare robots for rare events safely. Algorithm development iterates rapidly using twins. Remote troubleshooting diagnoses issues without physical access. Performance optimization tests different parameters virtually. Integration testing validates new sensors or tools before hardware installation. Accident investigation recreates incidents using twin simulations.
