Autonomous self-driving robots are applied in precision farming, health care and industry. Traditionally, these robots follow external, installed infrastructure, such as induction wires or RFID tags in the floor. These techniques have certain drawbacks. There is a growing demand for industrial robots that can perform different tasks. The last years, we have seen the development of systems that can navigate based on laser scanners and maps of the environment. However, these solutions do not always handle changing environments or big areas. Moreover, these solutions are closed source, so it is costly to make changes to the system.
Accordingly, there is a demand for practical knowledge on autonomous mobile robots, that do not rely on external infrastructure. The robots should be able to adapt to different circumstances. It must be able to navigate autonomously and safely in areas with people and other robots. The consortium partners in the project want to work on an open solution, that can be applied to their own hardware. They aim for open solutions. The solutions should be adaptable for new environments. The development of stable, safe and autonomous mobile robot is a challenging task. The solution requires state of the art sensors to generate an image of the environment. Localization, planning, and navigation require complex algorithms that SMEs can't develop in house. It is important to investigate the applicability of open source solutions.
The Next Generation Navigation project is part of the autonomous systems research line of the Mechatronics research group. We build on the knowledge that was developed in the TFF project Medical Robotics, in the European project R5 Cop, in the TFF project SLAMming and in the TFF project MARIO. The previous project focused on smaller robots. In NeNa we further develop the knowledge and apply it to an industrial robot platform, together with nine partners: Demcon, Hencon, Hollander Techniek, Indes, Opteq Mechatronics B.V., Riwo, Romias, Singa and Wewo. The project develops practical knowledge and experience by collaboratively developing a robot test platform. After the project, the platform can be used to test other sensor systems for autonomous navigation.