Autonomous driving has achieved significant milestones in research and development over
the last two decades. There is increasing interest in the field as the deployment of …

We demonstrate the need and potential of systematically integrated vision and semantics
solutions for visual sensemaking in the backdrop of autonomous driving. A general …

Driving an automobile involves the tasks of observing surroundings, then making a driving
decision based on these observations (steer, brake, coast, etc.). In autonomous driving, all …

Driven by deep neural networks (DNN), the recent development of computer vision makes
vision sensors such as stereo cameras and Lidars ubiquitous in autonomous cars, robotics …

Qualitative spatial/temporal reasoning (QSR/QTR) plays a key role in research on human
cognition, eg, as it relates to navigation, as well as in work on robotics and artificial …

Abstract Qualitative Spatial & Temporal Reasoning (QSTR) is a major field of study in
Symbolic AI that deals with the representation and reasoning of spatiotemporal information …

Sensing and Perception (S&P) is a crucial component of an autonomous system (such as a
robot), especially when deployed in highly dynamic environments where it is required to …

In the last decade, there has been a growing interest in applying AI technologies to
implement complex data analytics over data streams. To this end, researchers in various …

Machine learning (ML) has significantly enhanced the abilities of robots, enabling them to
perform a wide range of tasks in human environments and adapt to our uncertain real world …

Due to advances in computing power and internet technology, various industrial sectors are
adopting IT infrastructure and artificial intelligence (AI) technologies. Recently, data-driven …