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

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

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 …

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

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 …

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

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 …

Autonomous driving has taken a leap in recent years due to the significant improvements in
convolutional neural networks and advanced video processing algorithms. Despite these …

Autonomous machines such as vehicles, drones, and robotic manipulators promise to
transform the world by unleashing humans from repetitive, dangerous, and labor-intensive …

Region-of-interest (ROI) and ground point filter is a vital pre-processing step that 1). reduces
computation and memory complexity of following perception tasks, and 2). identifies …