Estimation of structure and physical relations among multi-modal sensor variables for musculoskeletal robotic arm

Autonomous robots that work in the same environment as humans must operate safely and adapt to handle various tools and deal with partial malfunctions. We propose an approach for estimating the robot structure and apply this approach for building a controller of dynamic motions. The robot structure is estimated by evaluating the mutual information (MI) among the sensor variables. Variables with high values of MI are edge-connected and the controller is automatically constructed based on the estimated structure. The proposed approach can accommodate changes in the robot parameters and dynamic motions. We verify the proposed method by using a simulator of a musculoskeletal arm driven that is driven by artificial muscle for mechanical safety.