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.

翻译：本文提出了一种针对配备分布式定向传感器的关节机器人的新型性能度量指标——传感器可观测性分析。这些安装在机器人上的分布式定向传感器（如关节扭矩传感器）会随着关节运动改变各自的感测方向。SOA将关节空间中各传感器轴系进行变换，以提供这些传感器观测各任务空间轴系的累积感测质量，类似于传感器的正向运动学。例如，某些关节构型可能使关节扭矩传感器的排布方式导致其无法观测一个或多个任务空间轴系上的交互力。由此得到的传感器可观测性性能度量指标可用于优化和零空间控制，以避免传感器可观测性奇异构型，或在特定方向上最大化传感器可观测性。我们以串联机器人机械臂中的力传感为例展示该分析方法。研究揭示了传感器可观测性与传统运动学可操作度之间的对应关系；SOA在分析非关节安装传感器方面表现出更强的普适性，并可能应用于力传感之外的其他传感器类型。通过定制三自由度机器人和Baxter机器人进行的仿真与实验，验证了传感器可观测性在物理交互中的实用价值与重要性。