Unrestrained human arm trajectories between point targets have been investigated using a three-dimensional tracking apparatus, the Selspot system. Movements were executed between different points in a vertical plane under varying conditions of speed and hand-held load. In contrast to past results which emphasized the straightness of hand paths, movement regions were discovered in which the hand paths were curved. All movements, whether curved or straight, showed an invariant tangential velocity profile when normalized for speed and distance. The velocity profile invariance with speed and load is interpreted in terms of simplification of the underlying arm dynamics, extending the results of Hollerbach and Flash (Hollerbach, J. M., and T. Flash (1982) Biol. Cybern. 44: 67-77).

The inertial parameters of manipulator rigid-body loads and links have been automatically estimated as a result of gen eral movement. The Newton-Euler equations have been recast to relate linearly the measured joint forces or torques via acceleration-dependent coefficients to the inertial parame ters, which have then been estimated by least squares. Load estimation was implemented on a PUMA 600 robot equipped with an R TI FS-B wrist force-torque sensor and on the MIT Serial Link Direct Drive Arm equipped with a Barry Wright Company Astek wrist force-torque sensor. Good estimates were obtained for load mass and center of mass, and the forces and torques due to movement of the load could be pre dicted accurately. The load moments of inertia were more difficult to estimate. Link estimation was implemented on the MIT Serial Link Direct Drive Arm. A good match was ob tained between joint torques predicted from the estimated parameters and the joint torques estimated from motor cur rents. The match actually proved superior to predicted torques based on link inertial parameters derived by CAD modeling. Restrictions on the identifiability of link inertial parameters due to restricted sensing and movement near the base have been addressed. Implications of estimation accu racy for manipulator dynamics and control have been consid ered.

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The paper studies the properties of a sinusoidally vibrating wedge billiard as a model for 2D impact juggling. It is shown that some periodic orbits that are unstable in the elastic fixed wedge become exponentially stable in the (non-)elastic vibrating wedge. These orbits are linked with some classical juggling patterns, providing an interesting benchmark for the study of the frequency-locking properties in human rhythmic tasks.

We present an algorithm that uses trajectory following errors to improve a feedforward command to a robot. This approach to robot learning is based on explicit modeling of the robot; and uses an inverse of the robot model as part of a learning operator which processes the trajectory errors. Results are presented from a successful implementation of this procedure on the MIT Serial Link Direct Drive Arm. The major point of this paper is that more accurate robot models improve trajectory learning performance, and learning algorithms do not reduce the need for good models in robot control.