On the base of the developed master-slave prosthetic hand-arm robot system, which is controlled mainly based on signals obtained from bending sensors fixed on the data glove, the first idea deduced was to develop and add a multi-dimensional filter into the original control system to make the control signals cleaner and more stable at real time. By going further, a second new idea was also proposed to predict new control information based on the combination of a new algorithm and prediction control theory. In order to fulfill the first idea properly, the possible methods to process data in real time, the different ways to produce Gaussian distributed random data, the way to combine the new algorithm with the previous complex program project, and the way to simplify and reduce the running time of the algorithm to maintain the high efficiency, the real time processing with multiple channels of the sensory system and the real-time performance of the control system were researched. Eventually, the experiment on the same provided robot system gives the results of the first idea and shows the improved performance of the filter comparing with the original control method.
翻译:在发达的万能假肢手臂机器人系统的基础上,主要根据固定在数据手套上的弯曲传感器获得的信号加以控制。 第一个设想是开发和在原始控制系统中增加一个多维过滤器,使控制信号更清洁,实时更稳定。进一步,还提出了第二个新想法,根据新的算法和预测控制理论的结合,预测新的控制信息。为了正确实现第一个设想,实时处理数据的可能方法、制作高森散射随机数据的不同方法、将新算法与前一个复杂程序项目相结合的方法,以及简化和缩短算法运行时间的方法,以保持高效率,实时处理传感器系统的多渠道和控制系统的实时性能。最后,对同一提供的机器人系统进行的试验提供了第一个设想的结果,并显示了与原始控制方法相比过滤器的改进性能。