Fujitsu Laboratories Ltd. has developed a learning system for humanoid robots that uses a dynamically reconfigurable neural network to enable efficient learning of movement and motor coordination.

The technology is based on Central Pattern Generator (CPG) networks, mimicking a function found in earthworms and lampreys that mathematically simulates a neural oscillator. This is combined with a numerical perturbation (NP) method that quantifies the configuration and connection-weight status of the network.

For a robot with 20 moveable joints, the learning time is reduced by 10³⁰ of the time previously required.

Fujitsu Laboratories Ltd. has developed a learning system for humanoid robots that uses a dynamically reconfigurable neural network to enable the efficient learning of movement and motor coordination.