Collision detection using band designed Disturbance Observer

In this work, we design frequency band filters in Disturbance Observer (DOB) for collision detection between the industrial robot manipulator and human. We realize that the frequency characteristics of the inverse dynamics of the manipulator is similar to that of high pass filter and the sensor noise filter is in the form of low pass filter whereas the collision between the robot and human is relatively high frequency. By investigating the frequency characteristics of each part of the manipulator and possible disturbances, we proposes a set of band-width filters using intrinsic data and detects the human-robot collision while the robot is in motion for performing some tasks. We verify the effectiveness of the method using two different types of robotic manipulators; electric motor driven manipulator and manipulator with hydraulic rotary actuators. In both cases, experimental data show that the robot-human collision can be detected reliably and faster than simply using a joint torque sensor while the manipulator load is not constant.