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.
翻译:提出了跳伞实时运动训练系统。 空中操作通过改变身体姿势进行,从而转移周围空气流。 自然学习过程非常缓慢, 原因是不熟悉自由落伏的动态, 压力诱使情感反馈受到阻碍, 以及所需运动的复杂性。 关键的想法是用一个自动控制系统来增强学习者, 如果直接进入学习者的身体作为导体, 就能进行训练后的活动。 辅助系统将向学习者提供以下视觉提示: 1. 现有身体姿势的反馈; 2. 使身体进行所需动作的身体姿势; 3. 如果身体保持目前姿势, 预测未来的惯性姿势和方向。 该系统将使新人能够在自由落伏和感知不熟悉环境的动态, 从而加速技能获取的初始阶段。 本文展示了“ 校对” 实验的结果, 即人类首次控制计算机模拟的虚拟天跳自由落。 没有辅助系统, 这项任务不可能完成任务, 使所有参与者都能完成任务。