Safety is the most important requirement for autonomous vehicles; hence, the ultimate
challenge of designing an edge computing ecosystem for autonomous vehicles is to deliver …

As the Internet of Things (IoT) continues its run as one of the most popular technology
buzzwords of today, the discussion really turns from how the massive data sets are collected …

Recent researches on robotics have shown significant improvement, spanning from
algorithms, mechanics to hardware architectures. Robotics, including manipulators, legged …

Simultaneous Localization and Map** (SLAM) is a critical task for autonomous navigation.
However, due to the computational complexity of SLAM algorithms, it is very difficult to …

To simultaneously enable multiple autonomous driving services on affordable embedded
systems, we designed and implemented LoPECS, a Low-Power Edge Computing System …

The agnostic robotic paradigm (ARP) represents a recent development as the use of robots
becomes more common, and there is a need for agnostic robots to cope with rich artificial …

Analysis of state-of-the-art visual odometry/visual simultaneous localization and map**
(VSLAM) system exposes a gap in balancing performance (accuracy and robustness) and …

We develop and commercialize autonomous machines, such as logistic robots and self-
driving cars, around the globe. A critical challenge to our—and any—autonomous machine …

This book provides a thorough overview of the state-of-the-art field-programmable gate array
(FPGA)-based robotic computing accelerator designs and summarizes their adopted …

With fully autonomous flight capabilities coupled with user-specific applications, drones, in
particular quadcopter drones, are becoming prevalent solutions in myriad commercial and …