Towards Safe Human-Robot Collaboration: Intelligent Collision Handling
In recent years, new trends in industrial manufacturing have changed the interaction patterns between humans and robots. Instead of the conventional isolation mechanism, close cooperation between humans and robots is more and more required for complicated tasks. The HR-Recycler project seeks a solution to allow close human-robot collaboration for the disassembly of electronic wastes within industrial environments. In such a scenario, humans and robots are sharing the same workspace, and the handling of unexpected collisions is among the most important issues of the HR-recycler system. To be more specific, the robot platform in a disassembly scenario should be able to appropriately detect an unexpected collision and measure its value, such that emergent reaction strategies can take over the task routine to prevent or mitigate possible damages and injuries. Moreover, the collisions should be distinguished from the demanded physical human-robot interactions (pHRI) or intentional contacts, such that the nominal disassembly tasks are not disturbed. Highly relevant to the HR-Recycler project, the Technical University of Munich (TUM) develops a novel collision-handling scheme for robot manipulators, which is able to precisely measure the collision forces without torque sensors and identify the collision types with incomplete waveforms. The scheme provides a reliable solution to guarantee the safety of the HR-Recycler robot in complicated environments.
Collision Force Estimation without Torque and Velocity Measurements
When an unexpected collision occurs between the robot and the human or the environmental objects, the collision forces are exerted on the robot joints, which can be used to evaluate the effects of the collision. Although force sensors can be installed on the robot to measure the collision forces, they are usually quite expensive for low-cost robot platforms, such as the recycling robots. Thus, TUM proposes a novel method to estimate the collision forces using system dynamics without torque sensors (https://bit.ly/3eUuDD7). Different from the conventional collision force estimation methods, the usage of velocity measurement is also avoided, which improves the estimation response to the differential noise. In general, the method provides a solution for measuring collisions for low-expense robots with incomplete sensory. The method can be used to implement a force-feedback admittance control without force measurement (See Figure 1), which, conventionally, can only be achieved using high precision force sensors.
Figure 1. The application of the collision force estimation method to a force-feedback admittance control in safe HRC. (a). Robot in a nominal task. (b). An external force exerted on the robot. (c). Admittance behavior of the robot to the external force for safety. (d). Robot back to the nominal task after the vanishing of the external force.
Intelligent Collision Classification with Incomplete Force Waveform
There are two basic types of physical contacts in HRC scenarios that are commonly considered. The accidental collisions are unexpected pHRI featured with fast changes and are dangerous to humans, while the intentional contacts are demanded physical contacts possessing gentle waveform and are safe in HRC scenarios. In a disassembly scenario of the HR-Recycler, an accidental collision can be a collision with the human or an undesired workpiece, and an intentional contact may be the human-teaching procedure to manually adjust the robot’s posture. These two kinds of pHRI usually lead to different consequences and should be classified to trigger different safety mechanisms. TUM develops an intelligent collision classification scheme using supervised learning methods (https://bit.ly/2IwpqWk). To adapt the method to the online application, a Bayesian decision method is used to improve the classification accuracy with incomplete signals. The method provides a fast, reliable, and intelligent scheme to identify collisions from safe pHRI, and can be used to trigger different safe reaction strategies (See Figure 2) for the sake of flexible and adaptive HRC, which benefits a low-cost but reliable collision-handling mechanism for HR-recycler robots.
Figure 2. The application of the intelligent collision classification method in a flexible collision handling procedure. (a). A human-robot collision occurs. (b). Collision is identified and an emergent stop is triggered. (c). A safe intentional human-robot contact is exerted. (d). Safe contact is classified and the robot teaching procedure is automatically enabled.
M.Sc. Salman Bari
Research Associate
Chair of Automatic Control Engineering (LSR)
Faculty of Electrical Engineering & Information technology
Technical University of Munich (TUM)
80333 Munich, Germany
