How to make a self-driving truck see: from DARPA challenge to nowadays
Evocargo
About speaker
I am a Research Engineer at Evocargo as well as a Mathematician and Computer Vision enthusiast. As a research engineer at Evocargo, I have gained extensive knowledge and hands-on experience in the development of LiDAR perception systems for autonomous vehicles. At Evocargo, we are pioneering the manufacturing and implementation of autonomous all-electric/hydrogen-based “in hub” delivery vehicles, which require advanced and robust LiDAR perception systems for safe and efficient navigation. Through my work at Evocargo, I have tackled various challenges related to LiDAR perception, particularly in adverse weather conditions. This experience has equipped me with a deep understanding of the technical requirements and best practices for successful LiDAR perception in autonomous driving.
About speakers's company
Evocargo is an innovative global logistics company and a pioneer in manufacturing and implementing autonomous all-electric/hydrogen-based "in hub" delivery vehicles in indoor and outdoor premises.
4 July, 10:00, «Hall 2»
Abstracts
Join me to discover how to create a self-driving truck, solve perception tasks using deep learning and LiDARs, and what challenges LiDAR perception faces in the unique driving conditions of the UAE and beyond the polar circle.
Self-driving cars are set to change the future of transportation. LiDARs, along with cameras and other sensors, are the eyes of self-driving cars, providing unparalleled accuracy and precision in perceiving the environment around them, and enabling safer and more efficient navigation. In my talk, I will explain how Evocargo is solving object detection and semantic segmentation tasks, as well as challenges that perception faces in the diverse weather conditions in different locations: from the UAE to the polar circle.
The talk was accepted to the conference program
