Abstract. To explore issues of developmental structure, physical embodiment, integration of multiple sensory and motor systems, and social interaction, we have constructed an upper-torso humanoid robot called Cog. The robot has twenty-one degrees of freedom and a variety of sensory systems, including visual, auditory, vestibular, kinesthetic, and tactile senses. This chapter gives a background on the methodology that we have used in our investigations, highlights the research issues that have been raised during this project, and provides a summary of both the current state of the project and our long-term goals. We report on a variety of implemented visual-motor routines (smooth-pursuit tracking, saccades, binocular vergence, and vestibular-ocular and opto-kinetic reflexes), orientation behaviors, motor control techniques, and social behaviors (pointing to a visual target, recognizing joint attention through face and eye finding, imitation of head nods, and regulating interaction through expressive feedback). We further outline a number of areas for future research that will be necessary to build a complete embodied system. 1

Contents: 46 pages, including 1 appendix, 1 table, and 16 gures.

A novel obstacle avoidance paradigm was used to investigate the planning of human reaching movements. We explored whether the CNS plans arm movements based entirely on the visual space kinematics of the movements, or whether the planning process incorporates specific details of the biomechanical plant to optimize the trajectory plan. Participants reached around an obstacle, the tip of which remained fixed in space throughout the experiment. When the obstacle and the start and target locations were rotated about the tip of the obstacle, the visually specified task constraints retained a rotational symmetry. If movements are planned in visual space, as indicated from a variety of studies on planar point-to-point movements, the resulting trajectories should also be rotation-Many of the motor tasks facing the CNS are characterized by extrinsic (visual space) constraints, which are insufficient to identify

The pattern of muscle responses associated with catching a ball in the presence of vision was investigated by inciependently varying the height of the drop and the mass of the ball. It was found that the anticipatory EMG responses comprised early and late components. The early components were produced at a roughly constant latency (about 130 msec) from the time of ball release. Their mean amplitude decreased with increasing height of fall. Late components represented the major build-up of muscle activity preceding the impact and were accompanied by limb flexion. Their onset time was roughly constant (about 100 msec) with respect to the time of impact (except in wrist extensors). This indicates that the timing of these responses was based on an accurate estimate of the instantaneous values of the time-to-contact (time remaining before impact).

Theoretical and psychophysical studies have suggested that humans learn to make reaching movements in novel dynamic environments by building specific internal models (IMs). Here we have found electromyographic correlates of internal model formation. We recorded EMG from four muscles as subjects learned to move a manipulandum that created systematic forces (a “force field”). We also simulated a biomechanical controller, which generated movements based on an adaptive IM of the inverse dynamics of the human arm and the manipulandum. The simulation defined two metrics of muscle activation. The first metric measured the component of the EMG of each muscle that counteracted the force field. We found that early in training, the field-appropriate EMG was driven by an error feedback signal. As subjects practiced, the peak of the field-appropriate EMG shifted temporally to earlier in the movement,

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When a perturbation displaces the human hand from equilibrium, arm muscles respond by producing restoring forces. When a set of displacements are given at various directions from the same equilibrium position, the resulting restoring forces form a #postural force #eld." It is not known whether these postural forces are related to those generated when a reaching movement is executed. However, if a movement is a consequence of a shift of the equilibrium position of the hand toward the target, then, from the postural force #eld, predictions can be made regarding the nature of the elastic forces acting on the hand during the movement. Wehave taken the #rst steps in testing this hypothesis by measuring the postural force #eld of a subject's arm over relatively large distances, and comparing these forces with the static forces generated at the hand while the subject attempted a reaching movement. Using a robot manipulandum, the hand was displaced at various directions from an equilibrium po...

Weinvestigated how the CNS learns to control movements in different dynamical conditions, and how this learned behavior is represented. In particular, we considered the task of making reaching movements in the presence of externally imposed forces from a mechanical environment. This environmentwas a force field produced by a robot manipulandum, and the subjects made reaching movements while holding the end--effector of this manipulandum. Since the force field significantly changed the dynamics of the task, subjects' initial movements in the force field were grossly distorted compared to their movements in free space. However, with practice, hand trajectories in the force field converged to a path very similar to that observed in free space. This indicated that for reaching movements, there was a kinematic plan independent of dynamical conditions.

The aim of this article is to describe the role of some neural mechanisms in the adaptive control of limb compliance dur-ing preplanned mechanical interaction with objects. We studied the EMG responses and the kinematic responses evoked by pseudorandom perturbations continuously ap-plied by means of a torque motor before and during a catch-ing task. The temporal changes of these responses were studied by means of an identification technique for time-varying systems. We found a transient reversal of EMG stretch reflex responses centered on the time of ball impact on the hand; this reversal results in a transient coactivation of an-tagonist muscles at both the elbow and the wrist. The kine-matic responses describe the relation between torque input and position output. Thus, they provide a global measure of limb compliance. The changes in limb compliance during

Although the orientation of an arm in space or the static view of an object may be represented by a population of neurons in complex ways, how these variables change with movement often follows simple linear rules, reflecting the underlying geometric constraints in the physical world. A theoretical analysis is presented for how such constraints affect the average firing rates of sensory and motor neurons during natural movements with low degrees of freedom, such as a limb movement and rigid object motion. When applied to nonrigid reaching arm movements, the linear theory accounts for cosine directional tuning with linear speed modulation, predicts a curl-free spatial distribution of preferred directions, and also explains why the instantaneous motion of the hand can be recovered from the neural population activity. For three-dimensional motion of a rigid object, the theory predicts that, to a first approximation,