Max Robotics — Global Service Robot Directory + US Certification

About

Iris Wieser is a robotics researcher whose work bridges autonomous navigation, multi-agent coordination, and human–robot interaction. Her key research areas include indoor localization, robotic exploration, and assistive robotics. Wieser made significant contributions to autonomous robotic SLAM-based indoor navigation, demonstrating how robots can achieve high-resolution, complete coverage of environments by leveraging magnetic field maps—a breakthrough that eliminates the need for pre-existing infrastructure. Her 2014 paper on this topic (14 citations) remains influential in the field of infrastructure-free localization. Wieser also advanced multi-agent exploration with Gaussian Processes (8 citations), providing a scalable algorithm for teams of robots to efficiently map unknown scalar or vector fields. In aerial robotics, she developed a robust collision avoidance layer using acoustic sensors (10 citations), enhancing flight safety for complex autonomous missions. Notably, her work on a robotic home assistant with memory aid functionality (16 citations) showcases her commitment to applying robotics to improve quality of life. Through these contributions, Wieser has demonstrated how principled algorithmic design can enable robots to navigate, explore, and assist in real-world environments with greater autonomy and reliability.