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The goal of this study was to evaluate different learning conditions for motor skill transfer. The study was divided into two experiments with the same task: learning a 3D trajectory with accuracy. The first experiment was focused on evaluating the efficiency of three feedback schemes for the target trajectory: visual, haptic and visual-haptic feedback. The second experiment was focused on analyzing the influence of decreasing the feedback during the training process. The results suggest that the best learning condition for learning a 3D trajectory with accuracy is to provide visual-haptic feedback, which facilitates the understanding of the dimension and orientation of each trajectory segment and solves any visual discrepancies that may exist. Furthermore, although continuous feedback can create dependences in users and impede the transfer of motor skills, feedback based on user request can also be dangerous since users can create a wrong mental representation that keep them from replicating the trajectory accurately. Therefore, when the performance of a task depends on references created during the training process, it seems appropriate for the system to provide automatic feedback based on user performance.

Virtual Environments using haptic devices have proved useful for assembly/disassembly simulation of mechanical components. To date most haptic virtual environments are stand-alone. Collaborative Haptic Virtual Environments (CHVEs) are distributed across a number of users via a network, such as the Internet. These present new challenges to the designer, such as consistency of the virtual environments, user-user haptic interaction, and scalability. The system described in this paper considers the CHVEs to be distributed over a packet-switched network such as the Internet. It gives priority to the validation of interactions between objects grasped by users; guarantees consistency across different users' virtual environments. The paper explains the components used and the consistency-maintenance scheme that guarantees the consistency of the virtual scene in the remote nodes. Consistency and force feedback results are also discussed. Results presented show the system maintains a consistent and satisfactory response when network incurs delay or packet jitter.