PhD stipend, Safe Learning Based Multi-Robot Planning and Control under Connectivity Constraints

The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of Safe Learning Based Multi-Robot Planning and Control under Connectivity Constraints within the general study programme Electrical and Electronic Engineering; starting on 1 February 2027, or as soon as possible thereafter. The PhD Fellow will be based at the Automation and Control Section in Aalborg. You can read more about the department at www.es.aau.dk. **Description of the position** How can a team of autonomous robots operate safely and make progress when communication deteriorates, the environment is only partially known, and the team must continually reorganize? This PhD position addresses this challenge through research on safe and resilient planning, control, and coordination of heterogeneous robotic systems in demanding underground environments. The position combines scientific research with substantial hands-on engineering. You will develop and analyse new algorithms, implement robotic software, build realistic simulation and digital-twin environments, and carry out systematic experiments with physical robot platforms. We are looking for a researcher who enjoys connecting mathematical ideas to reliable real-world robotic systems. **Description of the project** The ROX6G EU Horizon project aims to develop autonomous robotic systems for exploring and collecting data in hazardous, poorly documented underground mines. Its heterogeneous robot teams combine exploration, mapping, sensing, and sampling with mobile, multi-hop 5G/6G connectivity. Because robots also act as communication nodes, they must adapt their movement and team roles to sustain communication without relying on fixed infrastructure installed throughout the mine. The project is coordinated by AAU. In addition, within ROX6G, AAU leads the activities on learning based multi-robot coordination and reconfiguration for connectivity preservation and on digital-twin generation and multimodal visualization. The PhD candidate will contribute to both activities, collaborating with international partners across robotics, communications, sensing, and geological modelling. The main core of the PhD will focus on developing theoretical, algorithmic, and real-time implementation framework for on the fly autonomy of multi-robot control systems in uncertain and limited environments. In addition, methods will be evaluated through simulation, laboratory experiments, and project-level system integration and validation, with attention to safety, connectivity, and practical mission performance. **Your work tasks** The PhD fellow will be responsible for: - Conducting research on safe and resilient learning based planning, control, and coordination of multi-robot systems operating under constraints and uncertainty. - Actively contributing to the formulation and refinement of research questions within the doctoral project. - Taking an active role in planning, implementing, and, when necessary, adapting the research plan. - Designing, implementing, and evaluating the developed algorithms in realistic robotic simulation environments and on physical robotic platforms. - Contributing to the development and implementation of digital twins by integrating robotic sensor data, to support real-time visualization, monitoring, and autonomous decision-making. - Publishing research results in leading international journals and conferences, and presenting findings at project meetings and international scientific venues. **Your competencies** The successful candidate will hold a Masters degree in Robotics, Electrical Engineering, Control Engineering, Computer Science, or a closely related field, with a strong foundation in robotics, autonomous systems, planning, and/or control theory. We particularly value strong programming skills in Python and/or C++, familiarity with robotic software frameworks such as ROS/ROS 2, and demonstrated ability to implement, integrate, test, and troubleshoot robotic systems. Motivation for hands-on work with physical robot platforms, sensors, simulation, and experimental setups is important for this position. Experience with one or more of the following areas will be an advantage: multi-robot systems and graph-based coordination; safety-critical, robust, or optimisation-based control; autonomous navigation, localisation, simultaneous localisation and mapping (SLAM), or sensor fusion; simulation and digital-twin development using tools such as Gazebo, Isaac Sim, or Webots. Experience with data processing and visualisation, real-time robotic experiments, and research publications will also be considered positively. Applicants are not expected to have expertise in all these areas, but should be willing to learn and work across disciplines. You should be able to work independently and collaboratively in an international research environment, approach technical challenges in a structured and self-driven manner, and communicate clearly in written and spoken English. **Qualification requirements** PhD stipends are allocated to individuals who hold a Master's degree. PhD stipends are normally for a period of 3 years. It is a prerequisite for allocation of the stipend that the candidate will be enrolled as a PhD student at the Technical Doctoral School of IT and Design in accordance with the regulations of Ministerial Order No. 1039 of August 27, 2013 on the PhD Programme at the Universities and Certain Higher Artistic Educational Institutions. According to the Ministerial Order, the progress of the PhD student shall be assessed at regular points in time. **Who we are** The Department of Electronic Systems at Aalborg University (AAU) conducts internationally recognised research and education across digital technologies, including robotics, AI, control systems, communications, sound, and cybersecurity. Within the department, the Advanced Robotics & AI research group advances self-learning autonomous robotic systems for reliable operation in extreme environments. Our research strengthens robotic autonomy and resilience, enabling systems to operate safely and with minimal supervision in challenging settings. **Contacts** - Associate Professor Shahab Heshmati-Alamdari: shhe@es.aau.dk - Lisbeth Diinhoff: ld@adm.aau.dk