In this paper, we present an accelerometer-based kinematic calibration algorithm to accurately estimate the pose of multiple sensor units distributed along a robot body. Our approach is self-contained, can be used on any robot provided with a Denavit-Hartenberg kinematic model, and on any skin equipped with Inertial Measurement Units (IMUs). To validate the proposed method, we first conduct extensive experimentation in simulation and demonstrate a sub-cm positional error from ground truth data --an improvement of six times with respect to prior work; subsequently, we then perform a real-world evaluation on a seven degrees-of-freedom collaborative platform. For this purpose, we additionally introduce a novel design for a stand-alone artificial skin equipped with an IMU for use with the proposed algorithm and a proximity sensor for sensing distance to nearby objects. In conclusion, in this work, we demonstrate seamless integration between a novel hardware design, an accurate calibration method, and preliminary work on applications: the high positional accuracy effectively enables to locate distributed proximity data and allows for a distributed avoidance controller to safely avoid obstacles and people without the need of additional sensing.
翻译:在本文中,我们提出了一个基于加速计的运动校准算法,以准确估计在机器人身体上分布的多个传感器单元的构成。我们的方法是自成一体的,可以用于任何配备Denavit-Hartenberg运动模型的机器人,以及任何配备惰性测量单元(IMUs)的皮肤。为了验证拟议方法,我们首先在模拟中进行广泛的实验,并从地面真实数据中展示一个次厘米定位错误 -- -- 相对于先前的工作而言,改进了六次;随后,我们随后对一个7度自由合作平台进行了真实世界评估。为此目的,我们还采用了一种新型设计,用于配备IMU的单人造皮肤,与拟议的算法和感测距离近距离近距离物体的近距离传感器一起使用。在这项工作中,我们展示了新型硬件设计、精确校准方法和应用的初步工作:高定位精确度能够定位分布的近距离数据,并允许分布式的避险控制器安全地避免障碍和不需要额外感测的人。