  This paper presents a -- Learning from Demonstration -- method to perform
robot movement trajectories that can be defined as you go. This way
unstructured tasks can be performed, without the need to know exactly all the
tasks and start and end positions beforehand. The long-term goal is for
children with disabilities to be able to control a robot to manipulate toys in
a play environment, and for a helper to demonstrate the desired trajectories as
the play tasks change. A relatively inexpensive 3-DOF haptic device made by
Novint is used to perform tasks where trajectories of the end-effector are
demonstrated and reproduced. Under the condition where the end-effector carries
different loads, conventional control systems possess the potential issue that
they cannot compensate for the load variation effect. Adaptive tracking control
can handle the above issue. Using the Lyapunov stability theory, a set of
update laws are derived to give closed-loop stability with proper tracking
performance.
