Kim Min Su, Lee Jae Geun, Kang Soon Ju
Departement of Software Convergence, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 702-701, Korea.
School of Electronics Engineering, College of IT Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 702-701, Korea.
Sensors (Basel). 2016 Jun 8;16(6):842. doi: 10.3390/s16060842.
In the near future, we can expect to see robots naturally following or going ahead of humans, similar to pet behavior. We call this type of robots "Pet-Bot". To implement this function in a robot, in this paper we introduce a self-organizing interaction and synchronization method between wearable devices and Pet-Bots. First, the Pet-Bot opportunistically identifies its owner without any human intervention, which means that the robot self-identifies the owner's approach on its own. Second, Pet-Bot's activity is synchronized with the owner's behavior. Lastly, the robot frequently encounters uncertain situations (e.g., when the robot goes ahead of the owner but meets a situation where it cannot make a decision, or the owner wants to stop the Pet-Bot synchronization mode to relax). In this case, we have adopted a gesture recognition function that uses a 3-D accelerometer in the wearable device. In order to achieve the interaction and synchronization in real-time, we use two wireless communication protocols: 125 kHz low-frequency (LF) and 2.4 GHz Bluetooth low energy (BLE). We conducted experiments using a prototype Pet-Bot and wearable devices to verify their motion recognition of and synchronization with humans in real-time. The results showed a guaranteed level of accuracy of at least 94%. A trajectory test was also performed to demonstrate the robot's control performance when following or leading a human in real-time.
在不久的将来，我们有望看到机器人能像宠物一样自然地跟在人类身后或走在人类前面。我们将这类机器人称为“宠物机器人”。为了在机器人中实现这一功能，在本文中我们介绍了一种可穿戴设备与宠物机器人之间的自组织交互与同步方法。首先，宠物机器人在无需任何人为干预的情况下机会性地识别其主人，也就是说机器人能自行识别主人的靠近。其次，宠物机器人的活动与主人的行为同步。最后，机器人经常会遇到不确定的情况（例如，当机器人走在主人前面但遇到无法做出决定的情况，或者主人想要停止宠物机器人的同步模式以放松时）。在这种情况下，我们采用了一种手势识别功能，该功能使用可穿戴设备中的三维加速度计。为了实现实时交互与同步，我们使用了两种无线通信协议：125千赫兹低频（LF）和2.4吉赫兹低功耗蓝牙（BLE）。我们使用宠物机器人原型和可穿戴设备进行了实验，以验证它们对人类动作的实时识别和与人类的同步情况。结果显示准确率至少达到了94%的保证水平。还进行了轨迹测试，以展示机器人在实时跟随或引领人类时的控制性能。
