Vehicle Systems
Mix and match building blocks to build complex systems. YonoArc provides an easy-to-use drag-and-drop interface to build and evaluate complex systems consisting of many building blocks, fully abstracted from their different runtime environments and resource requirements.
It is challenging to build complex systems, such as autonomous vehicles, consisting of many building blocks (e.g., lane detection, object detection) without having to implement each and every block. It is always essential to benchmark new blocks against the competition and evaluate their effect on the overall system. To tackle these challenges, use YonoArc to build and evaluate complex systems using a simple drag-and-drop interface, while being fully abstracted from the different runtime environments and hardware requirements of the blocks.
Reuse the state-of-art blocks published on YonoStore, the marketplace of Yonohub.
Integrate blocks developed using different technologies (e.g., C++, Python, ROS, Octave, and Matlab).
Use public or proprietary datasets representing different scenarios.
Visualize the results in a variety of ways, e.g., videos, charts, and LIDAR views.
Benchmark proprietary blocks against the competition and study their effects on the
overall system.
Build complex systems whose resource requirements are far beyond the capabilities of a single machine.
Handle geographically distributed datasets by deploying each block close
to the dataset it needs.
Scale up computationally intensive blocks by using multiple instances of the same block.