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The SFB/TR 8 actually shaped a new research field by extending a previous subfield of cognitive science with its own interdisciplinary techniques. The research covered fundamental questions: what are the specific requirements of reasoning about space and time, for acting in space, and for any form of interaction including communication in spatio-temporal domains? It has been a success story in all research lines from foundational research to applications of spatial cognition in robotics, interaction and communication. de) over the past 12 years jointly by the Universities of Bremen and Freiburg. The theoretical foundations and practical implications have been investigated from a cognitive perspective (i.e., from an information processing point of view) within the Sonderforschungsbereich/Transregio SFB/TR 8 Spatial Cognition ( spatial-cognition. They need to perceive their environments, make sense of their perceptions, and make interactions as embodied entities with other agents and their environment. Space and time are two of the most fundamental categories any human, animal, or other cognitive agent such as an autonomous robot has to deal with. The developed neurosymbolic framework is domain-independent, with the case of autonomous driving designed to serve as an exemplar for online visual sensemaking in diverse cognitive interaction settings in the backdrop of select human-centred AI technology design considerations. As use-case, we focus on the significance of human-centred visual sensemaking -e.g., involving semantic representation and explainability, question-answering, commonsense interpolation- in safety-critical autonomous driving situations. We evaluate and demonstrate with community established benchmarks KITTIMOD, MOT-2017, and MOT-2020. The method integrates state of the art in visual computing, and is developed as a modular framework that is generally usable within hybrid architectures for realtime perception and control. A general neurosymbolic method for online visual sensemaking using answer set programming (ASP) is systematically formalised and fully implemented. We demonstrate the need and potential of systematically integrated vision and semantics solutions for visual sensemaking in the backdrop of autonomous driving.
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