INERTIAL NAVIGATION SYSTEMS FOR MOBILE ROBOTS
INERTIAL NAVIGATION SYSTEMS FOR MOBILE ROBOTS
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DOI：
10.1109/70.388775
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发表时间：
1995-06-01
期刊：
影响因子：
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通讯作者：
DURRANTWHYTE, HF
中科院分区：
文献类型：
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作者：
BARSHAN, B;DURRANTWHYTE, HF
描述了一种用于移动的机器人应用的低成本固态惯性导航系统（INS）。惯性传感器的误差模型被生成并包含在扩展卡尔曼滤波器（EKF）中，用于估计移动机器人车辆的位置和方向。两种不同的固态陀螺仪进行了评估，估计的机器人的方向。将具有误差模型的陀螺仪的性能与从系统中排除误差模型时的性能进行比较。结果表明，在没有误差补偿的情况下，定向误差在5-15度/min之间，但是如果提供适当的误差模型，则可以至少改善5倍，已经为固态三轴加速度计的每个轴和也可以用作低成本加速度计的导电泡倾斜传感器开发了类似的误差模型，利用来自加速度计和倾斜传感器的信息的线性位置估计由于估计位置中涉及的双重积分过程而更容易受到误差的影响。利用这里描述的系统，位置漂移速率为1-8 cm/s，这取决于加速度变化的频率。本文介绍了一种由三个陀螺仪、一个三轴加速度计和两个倾角传感器组成的组合惯性平台。文中给出了该平台在一个大型室外移动的机器人系统上的试验结果，并与机器人自身的雷达制导系统的试验结果进行了比较。平台需要来自某种绝对位置感测机构的附加信息以克服长期漂移。然而，结果表明，仔细和详细的建模误差源，低成本的惯性传感系统可以提供有价值的方向和位置信息，特别是户外移动的机器人应用。
A low-cost solid-state inertial navigation system (INS) for mobile robotics applications is described, Error models for the inertial sensors are generated and included in an Extended Kalman Filter (EKF) for estimating the position and orientation of a moving robot vehicle. Two different solid-state gyroscopes have been evaluated for estimating the orientation of the robot. Performance of the gyroscopes with error models is compared to the performance when the error models are excluded from the system, The results demonstrate that without error compensation, the error in orientation is between 5-15 degrees/min but can be improved at least by a factor of 5 if an adequate error model is supplied, Similar error models have been developed for each axis of a solid-state triaxial accelerometer and for a conducting-bubble tilt sensor which may also be used as a low-cost accelerometer, Linear position estimation with information from accelerometers and tilt sensors is more susceptible to errors due to the double integration process involved in estimating position, With the system described here, the position drift rate is 1-8 cm/s, depending on the frequency of acceleration changes, An integrated inertial platform consisting of three gyroscopes, a triaxial accelerometer and two tilt sensors is described, Results from tests of this platform on a targe outdoor mobile robot system are described and compared to the results obtained from the robot's own radar-based guidance system, Like all inertial systems, the platform requires additional information from some absolute position-sensing mechanism to overcome long-term drift. However, the results show that with careful and detailed modeling of error sources, low-cost inertial sensing systems can provide valuable orientation and position information particularly for outdoor mobile robot applications.