We developed a real-time controller for a 2 degree-of-freedom robotic system using xPC Target. This system was used to investigate how different methods of performance error feedback can lead to faster and more complete motor learning in individuals asked to compensate for a novel visuo-motor transformation (a 30 degree rotation). Four groups of human subjects were asked to reach with their unseen arm to visual targets surrounding a central starting location. A cursor tracking hand motion was provided during each reach. For one group of subjects, deviations from the “ideal” compensatory hand movement (i.e. trajectory errors) were amplified with a gain of 2 whereas another group was provided visual feedback with a gain of 3.1. Yet another group was provided cursor feedback wherein the cursor was rotated by an additional (constant) offset angle. We compared the rates at which the hand paths converged to the steady-state trajectories. Our results demonstrate that error-augmentation can improve the rate and extent of motor learning of visuomotor rotations in healthy subjects. Furthermore, our results suggest that both error amplification and offset-augmentation may facilitate neuro-rehabilitation strategies that restore function in brain injuries such as stroke.

This paper presents an extension of stratified motion planning results to the case where the base manifold upon which the motion planning occurs is not smooth. Robotic applications of this work include motion planning for legged robots over known, nonsmooth terrain and manipulation of nonsmooth objects with multiple robotic manipulators.

This paper presents experimental demonstrations and verification of a vision-based stratified motion planning method for the case where the base manifold upon which the motion planning occurs is not smooth. Robotic applications of the method include motion planning for legged robotics over non-smooth (but known) terrain and manipulation of non-smooth objects with multiple robotic manipulators. Experimental results with multiple robots manipulating a common non-smooth object are presented.

Presents an extension of the authors' previous stratified motion planning results to the case where the base manifold upon which the motion planning occurs is not smooth. Robotic applications of this work includes motion planning for legged robots over non-smooth (but known) terrain and manipulation of non-smooth objects with multiple robotic manipulators.

This paper addresses a three-dimensional implementation that results in several separate manipulators, each with intermittent contact with a central object of known geometry, cooperatively manipulating the object to a desired new position and orientation. Rolling control of an object using redundant contact of several independent manipulators is made difficult by the hybrid nature of this system that introduces complexity to the trajectory-planning problem, and by imperfection in the kinematic models which are needed to achieve such trajectory planning. The former is a theoretical problem which has been solved using Lie-algebra-based strategies to plan motion for the stratified systems. Imperfection in the kinematic models, on the other hand, leads to a practical implementation problem since even small errors in the equations that relate the internal pose of the robot to the position of the end-effector make precise sustained contact with an object difficult. The consequent lack of control of contact force combined with frictional unpredictability associated with rolling, causes gradual growth in the disparity between actual and calculated position and orientation of the object. A robust means for applying vision to compensate for imperfections in the holonomic kinematics of the robots as well as to update estimates of the pose of the object is outlined. Experimental results are also presented.

This paper presents the development and experimental verification of a general control framework for robotic grasping and manipulation problems where "fingers" manipulate a grasped object. The method is general in that it is independent of object and finger geometries. Application of the method in simulation and to a real experimental platform are presented.