Study on networked collaboration using haptic devices

由于最近通信网络的进步，现在不仅传输语音和图像等传统媒体，而且传输其他流媒体作为触觉信息变得现实。这是一项非常具有挑战性的任务，已经提出了一些在网络上使用触觉信息的实验结果。由于几乎所有的研究都是由机器人研究人员社区进行的，他们“无辜地”忽略了延迟、抖动和丢包。也就是说，他们认为网络是理想的。然而，现实的网络并不理想，网络损伤导致触觉应用的服务质量(Quality of Services，Qos)严重恶化。从这个角度出发，我们研究了网络损伤，特别是时延、抖动和丢包对互联网上的触觉协作的影响。例如，我们发现100毫秒的延迟在触觉协作中非常关键，如果它超过100毫秒，我们就无法以任何方式保持良好的服务质量。在此基础上，提出了应对此类损害的几点对策。针对丢包问题，提出了一种实用的航位推算方法。针对带宽的局限性，提出了一种基于航位推算和二阶预测的带宽压缩方法。针对抖动，我们首先提出了一种实用的媒体内同步机制。我们还提出了一种媒体间同步机制。最后，我们将上述对策集成到一个实际的系统中。它非常健壮，而且令人高兴，它现在正被广泛用于网络触觉协作系统中对抗网络损伤的事实。

Owing to recent advance of communication networks, it is now becoming realistic to transmit not only conventional media like voice and images but also other streaming media as haptic information. This is a very challenging task and a few experimental result of the usage of haptic information over networks have been proposed. Since almost all the researches were by the community of researchers on robotics, they "innocently" ignored the delay, jitter and packet loss. Namely, they treated the network as ideal. However, the real networks are far from ideal and network impairment causes the heavy deteriation of Quality of Services (QoS) on haptic application. From this viewpoint, we study the effect of network impairment, especially delay, jitter and packet loss, on the haptics collaboration on Internet. For example, we found that delay of 100 [msec] is very crucial in haptic collaboration and if it is more than 100 [msec.], we cannot maintain good QoS in any way. Then, based on them, several countermeasures against such impairment were proposed. Against packet loss, we proposed a practical dead-reckoning method. Against, the limitation of bandwidth, we proposed a bandwidth compression method based on dead-reckoning and the 2nd order prediction. Against jitter, we first proposed a practical intra-media synchronization mechanism. We also proposed an inter-media synchronization mechanism. Finally, we integrated the above mentioned countermeasure into one practical system. It is very and robust and happily, it is now becoming widely used as the de-fact of the countermeasure against network impairment on networked haptic collaboration systems.