Abstract
This paper presents the potential of combining ROS (Robot Operating System), its state-of-art software, and EtherCAT technologies to design real-time robot control architecture for human–robot collaboration. For this, the advantages of an ROS framework here are it is easy to integrate sensors for recognizing human commands and the well-developed communication protocols for data transfer between nodes. We propose a shared memory mechanism to improve the communication between non-real-time ROS nodes and real-time robot control tasks in motion kernel, which is implemented in the ARM development board with a real-time operating system. The jerk-limited trajectory generation approach is implemented in the motion kernel to obtain a fine interpolation of ROS MoveIt planned robot path to motor. EtherCAT technologies with precise multi-axis synchronization performance are used to exchange real-time I/O data between motion kernel and servo drive system. The experimental results show the proposed architecture using ROS and EtherCAT in hard real-time environment is feasible for robot control application. With the proposed architecture, a user can efficiently send commands to a robot to complete tasks or read information from the robot to make decisions, which is helpful to reach the purpose of human–robot collaboration in the future.
Highlights
In recent years, human–machine collaboration has been an emerging field
The results show the actual position of motor follows the MoveIt planned path well and reaches the desired position (160 degree)
We highlight that our EtherCAT stack supports EtherCAT DC technology, which is a precision synchronization mechanism. Both authors use ROS packages for motion planning, but we provide a jerk-limited trajectory generation approach to obtain fine interpolation of MoveIt planned path to motor
Summary
Human–machine collaboration has been an emerging field. In the past, many companies believed that in order to achieve Industry 4.0, a fully automated production model in unmanned factories that replaced all humans with robots was required. Traditional automobile manufacturing vendors adopt thousands of industrial robots for full automation and mass production demands. Unlike these vendors above, many small and medium-sized vendors in the area of electronics manufacturing industry have other requirements to manufacture products with small amounts but customized specifications. In the human–machine collaboration mode, the relationship between humans and machines has changed from giving commands to working together; operators control and monitor production processes, while robots are responsible for repeated and dangerous works. With this cooperation mode of humans and machines, these factories will become more intelligent and efficient in practice. The development of collaborative robot control technologies is an essential topic
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