  A real-time motion training system for skydiving is proposed. Aerial
maneuvers are performed by changing the body posture and thus deflecting the
surrounding airflow. The natural learning process is extremely slow due to
unfamiliar free-fall dynamics, stress induced blocking of kinesthetic feedback,
and complexity of the required movements. The key idea is to augment the
learner with an automatic control system that would be able to perform the
trained activity if it had direct access to the learner's body as an actuator.
The aiding system will supply the following visual cues to the learner: 1.
Feedback of the current body posture; 2. The body posture that would bring the
body to perform the desired maneuver; 3. Prediction of the future inertial
position and orientation if the body retains its present posture. The system
will enable novices to maintain stability in free-fall and perceive the
unfamiliar environmental dynamics, thus accelerating the initial stages of
skill acquisition. This paper presents results of a Proof-of-Concept
experiment, whereby humans controlled a virtual skydiver free-falling in a
computer simulation, by the means of their bodies. This task was impossible
without the aiding system, enabling all participants to complete the task at
the first attempt.
