Editorial: Merging symbolic and data-driven AI for robot autonomy
Daniele Meli, Mohan Sridharan, Simona Perri, Nikos Katzouris · Frontiers in Robotics and AI · 2025
Robots are increasingly being deployed to assist humans in many applications such as medicine, 11 navigation, and industrial automation. To truly collaborate with humans in complex 12 environments, robots require advanced cognitive capabilities, including the ability to reason with 13 domain-specific commonsense knowledge and the noisy observations obtained in the presence of 14 partial observability and non-deterministic action outcomes. In summary, the contributions to this topic highlight the importance of merging symbolic and 80 data-driven AI methods in the context of robotics (and AI). These papers demonstrate how such 81 hybrid frameworks enable robots to reason with complex cognitive theories and noisy 82 multimodal sensor observations to achieve reliable, efficient, and transparent scene 83 understanding, planning, diagnostics, and human-robot collaboration in complex simulated and 84