用于最大化铰接机器人任务空间可观测性的传感器可观测性分析
Sensor Observability Analysis for Maximizing Task-Space Observability of Articulated Robots
AI总结：
提出一种名为传感器可观测性分析（SOA）的新性能指标，通过将关节空间传感器轴变换至任务空间评估累积感知质量，可用于优化和零空间控制以避免奇异构型，并在3-DOF和Baxter机器人上验证了其有效性。
摘要：
我们为带有分布式方向传感器的铰接机器人提出了一种新颖的性能指标，称为传感器可观测性分析（SOA）。这些安装在机器人上的分布式方向传感器（例如关节扭矩传感器）会随着关节运动改变其各自的感知方向。SOA将关节空间中的各个传感器轴进行变换，以提供这些传感器对每个任务空间轴的累积感知质量，类似于传感器的正向运动学。例如，某些关节构型可能会使关节扭矩传感器以某种方式对齐，导致它们无法观测一个或多个任务空间轴上的交互力。由此产生的传感器可观测性性能指标随后可用于优化和零空间控制中，以避免传感器可观测性奇异构型或最大化特定方向上的传感器可观测性。我们以串联机器人机械臂中的力感知为例展示该分析。我们在传感器可观测性与传统运动学可操作性之间进行了类比；结果表明，SOA在分析非关节安装传感器方面更具通用性，并有可能应用于力感知以外的传感器类型。使用定制的3-DOF机器人和Baxter机器人进行的仿真和实验证明了传感器可观测性在物理交互中的实用性和重要性。
英文摘要：
We propose a novel performance metric for articulated robots with distributed directional sensors called the sensor observability analysis (SOA). These robot-mounted distributed directional sensors (e.g., joint torque sensors) change their individual sensing directions as the joints move. SOA transforms individual sensors axes in joint space to provide the cumulative sensing quality of these sensors to observe each task-space axis, akin to forward kinematics for sensors. For example, certain joint configurations may align joint torque sensors in such a way that they are unable to observe interaction forces in one or more task-space axes. The resultant sensor observability performance metrics can then be used in optimization and in null-space control to avoid sensor observability singular configurations or to maximize sensor observability in particular directions. We use the specific case of force sensing in serial robot manipulators to showcase the analysis. Parallels are drawn between sensor observability and the traditional kinematic manipulability; SOA is shown to be more generalizable in terms of analysing non-joint-mounted sensors and can potentially be applied to sensor types other than for force sensing. Simulations and experiments using a custom 3-DOF robot and the Baxter robot demonstrate the utility and importance of sensor observability in physical interactions.
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