Mobile Robotics - Safe Autonomy in Shared Industrial Environments
We are seeking an excellent candidate at the doctoral researcher level to develop perception, prediction, and planning methods that enable autonomous machines to operate safely in human-robot shared industrial spaces. The research will model how people and machines move through dynamic environments to support human detection and tracking, spatio-temporal mapping, long-horizon human-motion prediction, and planning under uncertainty. The methodological scope includes probabilistic modeling, SLAM/localization, spatio-temporal representations, and decision-making under uncertainty. The work is part of Autonomy without Fences (AwF, 2026–2029) and will be validated at real sites (ports, underground mines, logistics terminals) with Kalmar, Normet, Sandvik, and KWH Logistics.