Plan-Based Robot Control

Autonomous mobile robots with incomplete control and incomplete knowledge of their environment profit greatly from knowledge-level representation and reasoning for their rational and goal-oriented action: active sensing, sensor data disambiguation, performance optimization, human-robot co-operation, explanation – these and more aspects of robust and beneficial robot performance are impossible without applying some symbolic knowledge. However, intertwining in closed-loop and in real-time the faculties of knowledge-level reasoning, robot control, sensing and sensor data interpretation is a fundamental challenge in AI. Within this spectrum, research in the DFKI research department Plan-Based Robot Control (PBR) focuses on hybrid (task-level, spatio-temporal, hierarchical, probabilistic) planning, and we are developing control architectures to amalgamate it with multi-modal active sensing, learning-based methods for sensor data interpretation, object anchoring, multi-modal semantic mapping, and closed-loop plan execution and monitoring.

Applications of our basic research in several domains range from developing long-term autonomous robots to integrating the respective robotics technology for assisting humans in current automated processes. The most prominent application domain is agriculture: as a data-intensive as well as knowledge-intensive, highly digitalized area featuring uncertainty and dynamics, it facilitates AI technology to be profitably applied. The Osnabrück region offers an eco-system of innovative medium-sized ag-tech companies and research partners in agri-food, in which our respective research transfer is rooted.

Research thrives on diversity, complexity and variety. These values are important to us and we are striving to live them in our research group - especially regarding diversity in our team, we still see potential for improvement. We would like to expressly encourage you to apply for open positions, in particular if you do not yet feel sufficiently represented in our team.