Revolution in mobility: AI controlled robots conquer the Hannover Messe!

Revolution in mobility: AI controlled robots conquer the Hannover Messe!

Ilmenau, Deutschland - At the Hanover Messe, innovative AI-based perception software for autonomous robots is currently being presented. This software, which was developed by Qais Yousef and Professor PU Li, the head of the process optimization department, works as a central perception and control system. It precisely records the traffic situation and the surroundings of the robot and enables both proactive and reactive behavior. It is particularly noteworthy that the software not only analyzes the movements of pedestrians, but also their facial expressions, which enables a prediction of their intentions. This allows robots to change their routes at an early stage without having to brake abruptly. In addition, the software recognizes its surroundings, which includes sidewalk nature, weather and lighting conditions, through the use of a 2D camera. She can even communicate with traffic lights and evaluates the security of her forecasts for artificial intelligence (AI). These technologies are used in numerous areas such as delivery robots, sidewalk cleaning robots and assistance robots for visually impaired people. This is reported by the tu ilmenau .

In addition, the TU Ilmenau presents innovative solutions for energy -efficient private mobile networks, also called campus networks. These networks are specifically designed for the needs of individual users and support the future mobile phone standard 6G. A team under the direction of Professor Andreas Mitschele-Thiel has designed a 5G+campus network as a research platform for autonomous systems and industrial automation. The intelligent network technologies enable automated network control through intent-based networking, whereby network operators can formulate requirements in natural language, which the system then automatically implements. In addition, the open radio access network O-ran promotes manufacturer-independent network architectures and the integration of new mobile phone technologies. The software application to optimize energy consumption in the networks enables energy -efficient operation. Here, too, AI and Machine Learning are used for analysis and control of the network operation in real time.

challenges and solutions in autonomous driving

Although AI can offer many advantages in autonomous vehicles, there are considerable challenges that need to be met. Verena, 39 years old, plans to use an intelligent car for everyday family life. On a ten -hour trip, she noticed that the car accelerated on a country road over the speed limit of 60 km/h. The incident led to considerable concerns of their security and the reliability of the system. This raises important questions: How can artificial intelligence in vehicles be designed in such a way that they are safe, explainable and user -friendly? These questions are addressed, among other things, by the Federal Office for Information Technology (BSI), which develops technical guidelines and standards to ensure a safe AI.

Artificial intelligence in autonomous vehicles processes data in real time, this includes the course of the road, traffic signs and movements from other road users. However, in order to function correctly, AI systems must be trained thoroughly. A test run by US scientists in 2018 illustrated that a AI system misinterpreted a stop sign due to a misleading note. The decisions of the AI ​​systems are often difficult to understand, which can lead to security problems. It is therefore essential that AI systems can be checked and technical measures are implemented to defend attacks and to avoid malfunctions. The need for such measures is also driven by the bsi

The context of technology in road traffic