论文标题
低成本，高度可定制的解决方案，用于模块化机器人的位置估计
A Low-Cost, Highly Customizable Solution for Position Estimation in Modular Robots
论文作者
论文摘要
准确的位置传感对于机器人技术中的状态估计和控制很重要。可靠且准确的位置传感器通常昂贵且难以自定义。将它们纳入具有非常严格限制的系统（例如模块化机器人）特别困难。绘图点是低成本，可靠且高度可定制的位置传感器，但它们的性能高度取决于制造和校准过程。本文提出了一个Kalman滤波器，其开发了简化的观察模型，以处理导致使用低成本微控制器的非线性问题。此外，为模块化机器人Smores-EP提供了一种完整的解决方案，用于使用各种感应方式，包括制造，表征和估计。该解决方案可以很容易地适应广泛的应用。
Accurate position sensing is important for state estimation and control in robotics. Reliable and accurate position sensors are usually expensive and difficult to customize. Incorporating them into systems that have very tight volume constraints such as modular robots are particularly difficult. PaintPots are low-cost, reliable, and highly customizable position sensors, but their performance is highly dependent on the manufacturing and calibration process. This paper presents a Kalman filter with a simplified observation model developed to deal with the non-linearity issues that result in the use of low-cost microcontrollers. In addition, a complete solution for the use of PaintPots in a variety of sensing modalities including manufacturing, characterization, and estimation is presented for an example modular robot, SMORES-EP. This solution can be easily adapted to a wide range of applications.
