Sensor Observability Analysis for Maximizing Task-Space Observability of Articulated Robots

by   Christopher Yee Wong, et al.

In this paper, we propose a novel performance metric for articulated robotic mechanisms called the sensor observability analysis and the resulting sensor observability index. The goal is to analyse and evaluate the performance of robot-mounted distributed directional or axial-based sensors to observe specific axes in task space as a function of joint configuration. For example, joint torque sensors are often used in serial robot manipulators and assumed to be perfectly capable of estimating end effector forces, but certain joint configurations may cause one or more task-space axes to be unobservable as a result of how the joint torque sensors are aligned. The proposed sensor observability analysis provides a method to analyse the cumulative quality of a robot configuration to observe the task space, akin to forward kinematics for sensors. The resultant 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. Parallels are drawn between sensor observability and the traditional kinematic Jacobian for the particular case of joint torque sensors in serial robot manipulators. Compared to kinematic analysis using the Jacobian in serial manipulators, sensor observability analysis 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, e.g., link-mounted proximity sensors. 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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