FutureMapping: The Computational Structure of Spatial AI Systems
This addresses the problem of enabling advanced spatial perception for intelligent embodied devices, but it is incremental as it builds on existing SLAM and hardware trends.
The paper tackles the gap between the required visual perception performance for devices like augmented reality eyewear and consumer robots and current capabilities, predicting the evolution of SLAM into a general Spatial AI system through co-design of algorithms, processors, and sensors.
We discuss and predict the evolution of Simultaneous Localisation and Mapping (SLAM) into a general geometric and semantic `Spatial AI' perception capability for intelligent embodied devices. A big gap remains between the visual perception performance that devices such as augmented reality eyewear or comsumer robots will require and what is possible within the constraints imposed by real products. Co-design of algorithms, processors and sensors will be needed. We explore the computational structure of current and future Spatial AI algorithms and consider this within the landscape of ongoing hardware developments.