When robots move out of controlled laboratory environments and into the real world, they face pervasive uncertainty—from slippery mud and flexible branches to highly variable terrain. These challenges are particularly critical when it comes to physical contact: in one moment a robot may apply large forces, and in the next it may lose grip entirely.

In this lecture, Prof. Aaron M. Johnson (Carnegie Mellon University / Visiting Professor at TUM) will present how robots can cope with and even take advantage of uncertainty. Examples range from off-road driving in unfamiliar environments to agile locomotion through vegetation. The talk will provide insights into how uncertainty can be understood, reduced, and leveraged for the future of robotic systems.

Topic: Seminar
Time: September 9, 2025 | 4:00
Location: Georg-Brauchle-Ring 58, Room M001
(The TUM Room Finder will help you find the way.)

For more information: https://baiosphere.org/event/munich-ai-lecture-aaron-m-johnson-729/register