Despite many recent efforts, accelerating robotic computing is still fundamentally
challenging for two reasons. First, robotics software stack is extremely complicated …

As urban transportation increasingly impacts daily life, efficiently utilizing traffic resources
and develo** public transportation have become crucial for addressing issues such as …

Within the field of automated driving, a clear trend in environment perception tends towards
more sensors, higher redundancy, and overall increase in computational power. This is …

Autonomous Driving (AD) systems extensively manipulate 3D point clouds for object
detection and vehicle localization. Thereby, efficient processing of 3D point clouds is crucial …

Autonomous micromobility systems (AMS) such as low-speed minicabs and robots are
thriving. In AMS, multiple Deep Neural Networks execute in parallel on heterogeneous AI …

Over the last decade, researchers and the car industry became very active in the
deployment of driverless cars as they can greatly increase safety of the vehicle, rate of traffic …

The emerging trend of autonomous embedded systems minimizing human intervention has
raised new questions about continuously maximizing system energy efficiency faced with …

Autonomous vehicles (AVs) employ sophisticated computer systems and algorithms to
perceive the surroundings, localize, plan, and control the vehicle. With several available …

The processing requirement of autonomous vehicles (AVs) for high-accuracy perception in
complex scenarios can exceed the resources offered by the in-vehicle computer, degrading …

Traffic light and road sign violations significantly contribute to traffic accidents, particularly at
intersections in high-density urban areas. To address these challenges, this research …