A Neural Circuit Model for Prospective Control of Interceptive Reaching

Two prospective controllers of hand movements in catching -- both based on required velocity control -- were simulated. Under certain conditions, this required velocity controlled to overshoots of the future interception point. These overshoots were absent in pertinent experiments. To remedy this shortcoming, the required velocity model was reformulated in terms of a neural network, the Vector Integration To Endpoint model, to create a Required Velocity Integration To Endpoint modeL Addition of a parallel relative velocity channel, resulting in the Relative and Required Velocity Integration To Endpoint model, provided a better account for the experimentally observed kinematics than the existing, purely behavioral models. Simulations of reaching to intercept decelerating and accelerating objects in the presence of background motion were performed to make distinct predictions for future experiments.Vrije Universiteit (Gerrit-Jan van Jngen-Schenau stipend of the Faculty of Human Movement Sciences); Royal Netherlands Academy of Arts and Sciences; Defense Advanced Research Projects Agency and Office of Naval Research (N00014-95-1-0409

New CLEO Results for |V_cb| and |V_ub|

We report recent measurements from CLEO of the first two moments of the photon energy spectrum for b -> s gamma decays and the hadronic recoil mass in B -> X_c l nu. These physical quantities allow one to fix non-perturbative parameters occurring in calculations based on HQET and QCD. Predictions for semileptonic decay rates within this same framework depend in addition on the CKM matrix elements V_qq' governing quark mixing. We can thus extract |V_cb| from the inclusive semileptonic decay rate of B mesons, and |V_ub| from the lepton endpoint spectrum of B -> X_u l nu. Model dependence is reduced except for the assumption of quark-hadron duality. Finally, we update the classic measurement of |V_cb| from B -> D* l nu at zero recoil.Comment: To appear in the Proceedings of the 9th Int'l Symposium on Heavy Flavor Physics; some references updated her

Inter-Joint Coordination Deficits Revealed in the Decomposition of Endpoint Jerk During Goal-Directed Arm Movement After Stroke

It is well documented that neurological deficits after stroke can disrupt motor control processes that affect the smoothness of reaching movements. The smoothness of hand trajectories during multi-joint reaching depends on shoulder and elbow joint angular velocities and their successive derivatives as well as on the instantaneous arm configuration and its rate of change. Right-handed survivors of unilateral hemiparetic stroke and neurologically-intact control participants held the handle of a two-joint robot and made horizontal planar reaching movements. We decomposed endpoint jerk into components related to shoulder and elbow joint angular velocity, acceleration, and jerk. We observed an abnormal decomposition pattern in the most severely impaired stroke survivors consistent with deficits of inter-joint coordination. We then used numerical simulations of reaching movements to test whether the specific pattern of inter-joint coordination deficits observed experimentally could be explained by either a general increase in motor noise related to weakness or by an impaired ability to compensate for multi-joint interaction torque. Simulation results suggest that observed deficits in movement smoothness after stroke more likely reflect an impaired ability to compensate for multi-joint interaction torques rather than the mere presence of elevated motor noise

Quarkonium momentum distributions in photoproduction and B decay

According to our present understanding many $J/\psi$ production processes proceed through a coloured $c\bar{c}$ state followed by the emission of soft particles in the quarkonium rest frame. The kinematic effect of soft particle emission is usually a higher-order effect in the non-relativistic expansion, but becomes important near the kinematic endpoint of quarkonium energy (momentum) distributions. In an intermediate region a systematic resummation of the non-relativistic expansion leads to the introduction of so-called `shape functions'. In this paper we provide an implementation of the kinematic effect of soft gluon emission which is consistent with the non-relativistic shape function formalism in the region where it is applicable and which models the extreme endpoint region. We then apply the model to photoproduction of $J/\psi$ and $J/\psi$ production in $B$ meson decay. A satisfactory description of $B$ decay data is obtained. For inelastic charmonium photoproduction we conclude that a sensible comparison of theory with data requires a transverse momentum cut larger than the currently used 1 GeV.Comment: latex, 45 pages; (v2) some typos corrected, version to appear in PR

Goal Set Inverse Optimal Control and Iterative Re-planning for Predicting Human Reaching Motions in Shared Workspaces

To enable safe and efficient human-robot collaboration in shared workspaces it is important for the robot to predict how a human will move when performing a task. While predicting human motion for tasks not known a priori is very challenging, we argue that single-arm reaching motions for known tasks in collaborative settings (which are especially relevant for manufacturing) are indeed predictable. Two hypotheses underlie our approach for predicting such motions: First, that the trajectory the human performs is optimal with respect to an unknown cost function, and second, that human adaptation to their partner's motion can be captured well through iterative re-planning with the above cost function. The key to our approach is thus to learn a cost function which "explains" the motion of the human. To do this, we gather example trajectories from pairs of participants performing a collaborative assembly task using motion capture. We then use Inverse Optimal Control to learn a cost function from these trajectories. Finally, we predict reaching motions from the human's current configuration to a task-space goal region by iteratively re-planning a trajectory using the learned cost function. Our planning algorithm is based on the trajectory optimizer STOMP, it plans for a 23 DoF human kinematic model and accounts for the presence of a moving collaborator and obstacles in the environment. Our results suggest that in most cases, our method outperforms baseline methods when predicting motions. We also show that our method outperforms baselines for predicting human motion when a human and a robot share the workspace.Comment: 12 pages, Accepted for publication IEEE Transaction on Robotics 201

Sensory Motor Remapping of Space in Human-Machine Interfaces

Studies of adaptation to patterns of deterministic forces have revealed the ability of the motor control system to form and use predictive representations of the environment. These studies have also pointed out that adaptation to novel dynamics is aimed at preserving the trajectories of a controlled endpoint, either the hand of a subject or a transported object. We review some of these experiments and present more recent studies aimed at understanding how the motor system forms representations of the physical space in which actions take place. An extensive line of investigations in visual information processing has dealt with the issue of how the Euclidean properties of space are recovered from visual signals that do not appear to possess these properties. The same question is addressed here in the context of motor behavior and motor learning by observing how people remap hand gestures and body motions that control the state of an external device. We present some theoretical considerations and experimental evidence about the ability of the nervous system to create novel patterns of coordination that are consistent with the representation of extrapersonal space. We also discuss the perspective of endowing human–machine interfaces with learning algorithms that, combined with human learning, may facilitate the control of powered wheelchairs and other assistive devices

Nonperturbative Effects in Bˉ→Xsl+l−\bar B\to X_s l^+l^- for Large Dilepton Invariant Mass

We reconsider the calculation of ${\cal O}(\Lambda^2_{QCD}/m^2_b)$ nonperturbative corrections to $\bar B\to X_sl^+l^-$ decay. Our analysis confirms the results of Ali et al. for the dilepton invariant mass spectrum, which were in disagreement with an earlier publication, and for the lepton forward-backward asymmetry. We also give expressions for the ${\cal O}(\Lambda^2_{QCD}/m^2_b)$ corrections to the left-right asymmetry. In addition we discuss the breakdown of the heavy quark expansion near the point of maximal dilepton invariant mass $q^2$ and consider a model independent approach to this region using heavy hadron chiral perturbation theory. The modes $\bar B\to\bar Kl^+l^-$ and $\bar B\to\bar K\pi l^+l^-$, which determine the endpoint region of the inclusive decay, are analyzed within this framework. An interpolation is suggested between the region of moderately high $q^2$, where the heavy quark expansion is still valid, and the vicinity of the endpoint described by chiral perturbation theory. We also comment on further nonperturbative effects in $\bar B\to X_sl^+l^-$.Comment: 18 pages, LaTeX, 1 figur