A Prototyping Environment for Integrated Artificial Attention Systems
This work addresses the need for adaptable attention systems in robotics, though it is incremental as it builds on existing concepts without introducing new algorithms.
The paper tackles the challenge of developing adaptable artificial visual attention systems for robotics by introducing a flexible prototyping environment based on robotic middleware, enabling testing with various inputs, algorithms, and tasks.
Artificial visual attention systems aim to support technical systems in visual tasks by applying the concepts of selective attention observed in humans and other animals. Such systems are typically evaluated against ground truth obtained from human gaze-data or manually annotated test images. When applied to robotics, the systems are required to be adaptable to the target system. Here, we describe a flexible environment based on a robotic middleware layer allowing the development and testing of attention-guided vision systems. In such a framework, the systems can be tested with input from various sources, different attention algorithms at the core, and diverse subsequent tasks.