WHY:
====

Teleoperators in industry use different motion patterns (i.e. skills)
to achieve different goals. E.g. a concrete spraying opertator will
use large sweeping motions to build up layers slowly, or small
concentric circles to build up layers quickly. Training to achieve
expert status is prolonged and costly.

WHAT:
=====

How do we develop an appropriate shared control framework that assists
an operator to maintain a skill whilst ensuring (changing) environment
constriants?

HOW:
====

This paper proposes a model-based framework that plans motions which
respect a skill whilst ensuring environment constraints are
satisfied. The method uses a moving horizon estimation scheme to
classify the operators desired skill (i.e. intention), and then
optimizes a predicted trajectory using a nonlinear optimization
program in an model predictive control loop. The method can adapt to
changes in the operator intention and environment.