Kinematic networks distributed model for representing and regularizing motor redundancy
Biological Cybernetics
Reaching with multi-referential dynamical systems
Autonomous Robots
PerMIS '08 Proceedings of the 8th Workshop on Performance Metrics for Intelligent Systems
Teaching a humanoid robot to draw `Shapes'
Autonomous Robots
| Hi-index | 0.00 |
The subjective ease with which we move gracefully in constraint filled uncertain environments often masks the enormously complex integrative apparatus needed to spell synergy among the thousands of sensors, joints, musculo-skeletal units and neuronal populations that contribute to any act's planning and execution. In this paper, we apply the computational framework of passive motion paradigm [5] for task specific composition and coordination of the movements of a limb, network of limbs (e.g. left arm-waist-right arm) or networks of external objects coupled to the body of the 53 degrees of freedom humanoid robot 'iCub'. The basic PMP model is further extended by formulation of a pair of branching nodes that allow compositionality and transfer of force fields from one relaxation network to another. The generality of the proposed approach is further illustrated using simulations of whole body reaching (WBR) tasks from a quiet standing posture that recruits virtually all the joints of the upper limbs, lower limbs, and trunk, binding together a large number of degrees of freedom into a functional unit that combines a focal task (reaching a target with the hand) and a postural task (keeping the projection of the center of mass within the bipedal support area). Preliminary comparisons of the solutions generated by the computational model with the movements of human subjects performing similar WBR tasks are presented.