Driving safely requires fast analysis and swift reflexes. Over the last few decades, automotive vehicles have become more sophisticated, embedding autonomous safety measures designed to aid drivers. Features such as automatic emergency braking and lane assist help drivers be more cautious on the road. In a similar fashion, researchers at Saarland University, led by Professor Matthias Nienhaus, have developed intelligent wheels for various types of vehicles that anticipate a user’s intent, helping with pushing, stability during cornering, and maneuverability under load.
Professor Nienhaus and the team at Saarland University developed smart wheels, which use electric motors inside the wheels as both power sources and sensors, eliminating the need for additional sensor equipment. Early versions required a sensor handle, but the latest iterations, being showcased at this year's Hannover Messe Fair, work intuitively with just a light touch, sensing slight changes in force to accelerate, brake, or steer as needed.
The technology interprets micro-variations in how a user pushes or pulls, allowing systems beyond automotive vehicles, such as hand trolleys, strollers, hospital beds, and wheelchairs, to move more smoothly and effortlessly. With the electric motors handling much of the acceleration and deceleration, moving heavy or awkward loads becomes significantly easier. In previous models, a sensor handle served as the primary user interface and control hub, but recent breakthroughs have enabled handle-free operation for vehicles up to 100 kilograms, making the setup more user-friendly and cost-effective. For heavier loads, the smart wheels can still be paired with the sensor handle for optimal control.
The wheels’ motors generate measurement data that acts like sensory input. This reveals details about the wheel’s condition and the forces acting on it. By analyzing this data, the system can discern the user’s intended direction and adjust its assistance accordingly. The research team has developed algorithms and even filed patents to maximize the usefulness of this motor data while minimizing interference. Their work shows how motor signals can indicate force, position, and load distribution. This enables responsive and adaptive support.
Mathematical models and artificial intelligence are used to process motor data and command the appropriate level of assistance almost instantly. The microcontroller embedded in the system interprets the signals, delivering exact control over the wheels’ movement. All data transfer is handled via standard wiring, simplifying integration into existing vehicle designs. The team intends to partner with industry to bring this technology to commercial applications, enabling many types of wheeled vehicles to become more intuitive and supportive.
