In this project, the chairs of Machine Tools and Control Systems (WSKL) and Control Systems (LRS) at the RPTU's Kaiserslautern campus are working on a flexible and intuitive solution for the use of industrial robots. The project includes the following points:

• Setup of a demonstrator consisting of two robot modules and a manual workstation equipped with sensor technology.
• Combining intelligent sensor technology based on acceleration sensors and image processing to detect people in the working space.
• Development of flexible and real-time capable trajectory planning for cooperative and collaborative use of robots in a shared workspace.
• Implementation of a plug & produce concept for the three assembled modules.
• Expansion of the industrial control system using an app-based approach.

To ensure that SMEs, especially in the manufacturing industry, remain competitive in the market and to prevent the relocation of jobs to lower-wage countries, these companies must be enabled to achieve a higher degree of automation with as simple and rapid workflows as possible. It will not be effective to generally automate any workflow; instead, process steps should be intelligently distributed among automated systems, human-machine systems, or manual workstations. Small, lightweight, and compliantly designed robots (collaborative robots) fundamentally allow for a shared workspace between humans and robots. Thus, they are a primary means for SMEs to automate processes at many existing manual workstations and increase productivity in collaboration with humans. These robots operate without a designated or fenced off working area and stop movement upon collision, thereby preventing severe work accidents. However, currently, these systems do not offer comprehensive protection and have limited capabilities for collaboration with humans. From today's perspective, there is a lack of solutions that enable robots to act independently, intelligently, and intuitively, as well as to be easily operated without specific manufacturer training. Solutions are needed that allow robots to perceive their environment and make appropriate decisions to successfully achieve their defined goals. Since humans perform tasks intuitively and can replan their actions based on new information in a very short time, robots must be able to safely handle these situations so that human work is not disrupted and there is no substantial need for humans to adapt to the robot. Even though there is still a long way to go for formal safety certification, technical approaches should also be considered that can increase flexibility while ensuring practical safety.

The COVID-19 pandemic demonstrated how sudden changes in demand can lead to supply shortages. A common issue is rigid automated systems that cannot adapt to varying demand. In the future, flexibly manageable production modules will ensure the adaptation of production resources to current market situations.

In six work packages, the KoKoBot platform is established, and software components are developed.

WP 1: Planning and setup of the demonstrator

A modularly connectable demonstrator platform with two robot modules and a manual workstation is designed and set up.

WP 2: Human robot collaboration

Acceleration sensors combined with image processing enable the detection of human movements in the workspace. The data is further used to allow the robot arm to consciously avoid the human.

WP 3: Robot robot cooperation

Flexible trajectory planning allows robots to independently perform collision-free movement to a target object. The system is intended to be expandable by any number of robot modules.

WP 4: Communication and control architecture

First, automatic detection and identification of adjacent modules will be enabled. Furthermore, the developed software solutions will be executed as a kind of app on an industrial control system, demonstrating the possibility of software-based expansion of industrial controls.

WP 5: Integration and validation

Integration of the previous four WPs to present a functioning overall demonstrator.

WP 6: Transfer

Transfer of project knowledge, for example, through the partner network of SmartFactory Kaiserslautern, which accompanies the project as a cooperation partner.