Chinese LiDAR Developer RoboSense and Autonomous Driving Technology Provider Pony.ai Established Strategic Partnership, which is expected to cover areas including autonomous driving and smart transportation.
On October 12, RoboSense (Chinese: 速腾聚创), a leading provider of smart LiDAR sensor systems, announced that it had established a new strategic partnership with Pony.ai (Chinese: 小马智行), a global autonomous driving technology company. The two parties are expected to start a full business chain cooperation on autonomous driving and smart transportation.
Founded in 2014, RoboSense, specializes in LiDAR technologies and has the capacity to mass produce its advanced LiDAR products. It has won global recognition for its innovation capacity, which is evidenced by the awards including the AutoSens Awards, Audi Innovation Lab Champion and CES Innovation Award it received. Pony.ai, established in 2017, has a strong advantage in autonomous driving technologies and driving scene recognition model building.
"RoboSense and Pony.ai have followed the trends of the time and reached a comprehensive partnership that would complement each other's strengths and lead to a win-win result. It will not only help enhance RoboSense's technological advantage in LiDAR application, but also facilitate Pony.ai's R&D and application of autonomous driving technologies in a wider range of scenarios." said Qiu Chunchao, co-founder and CEO of RoboSense.
"LiDAR is a core hardware in the development of autonomous driving, and hardware iterations and technology upgrading always go together," said Lou Tiancheng, co-founder and CTO of Pony.ai. "Through this strategic partnership with RoboSense, Pony.ai will further tap into the autonomous driving industry so as to develop the best autonomous driving system solutions and intelligent transportation products."
The two companies will work together on developing LiDAR products tailored to customized scenarios, providing better smart city solutions for traffic management and promoting the commercialization and large-scale implementation of self-driving trucks.