  In reality, there is still much to be done for robots to be able to perform
manipulation actions with full autonomy. Complicated manipulation tasks, such
as cooking, may still require a person to perform some actions that are very
risky for a robot to perform. On the other hand, some other actions may be very
risky for a human with physical disabilities to perform. Therefore, it is
necessary to balance the workload of a robot and a human based on their
limitations while minimizing the effort needed from a human in a collaborative
robot (cobot) set-up. This paper proposes a new version of our functional
object-oriented network (FOON) that integrates weights in its functional units
to reflect a robot's chance of successfully executing an action of that
functional unit. The paper also presents a task planning algorithm for the
weighted FOON to allocate manipulation action load to the robot and human to
achieve optimal performance while minimizing human effort. Through a number of
experiments, this paper shows several successful cases in which using the
proposed weighted FOON and the task planning algorithm allow a robot and a
human to successfully complete complicated tasks together with higher success
rates than a robot doing them alone.
