Holistic Model of Cognitive Limbs for Dynamic Situations

Abstract

Cognitive object handling and manipulation are vital skills for humans and future humanoid robots. However, the fundamental bases of how our brain solves such tasks remain largely unknown. Here we provide a novel approach that describes the problem of limb movements in dynamic situations on an abstract cognitive level. The approach involves two main steps: i) Transformation of the problem from the limb workspace to the so-called handspace, which represents the limb as a point and obstacles as objects of complex shapes, and ii) Construction of a generalized cognitive map (GCM) in the handspace by a neural network simulating activation wave. The GCM enables tracing a trajectory to a target that can be followed by the limb, which ensures collision-free movement and target catching in the workspace. We validate our approach by numerical simulations on an avatar developed for a humanoid robot Poppy.