Chinese lidar maker Hesai Technology has entered into a strategic partnership with Keeta Drone, the autonomous delivery arm of Meituan, to supply solid-state lidar sensors for next-generation urban delivery drones, the companies said.
Under the agreement, Hesai will provide its second-generation FTX solid-state lidar for use in Keeta Drone’s future delivery platforms. The collaboration aims to support the expansion of low-altitude logistics networks by improving navigation accuracy, safety and reliability in dense urban environments.
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Keeta Drone operates autonomous delivery services across multiple Chinese cities, including Beijing, Shanghai, Shenzhen and Guangzhou, and has completed more than 740,000 deliveries to date. The company currently runs 65 active routes and focuses on transporting food, pharmaceuticals and other time-sensitive goods.
Hesai said the FTX lidar is designed to support all-weather and all-light operations, enabling drones to navigate in conditions such as rain, fog or low visibility without relying solely on cameras or satellite positioning. The system offers an ultra-wide field of view and improved detection of small obstacles such as power lines and tree branches.
Compared with its previous generation, the FTX lidar doubles resolution while reducing overall weight by about 66%, helping to lower the payload burden on drones and improve flight efficiency. The company said the sensor is scheduled to enter mass production in 2026.
Keeta Drone has begun integrating the technology into its fourth-generation M-Drone 4L platform, which combines lidar, vision sensors and GNSS for multi-sensor fusion. During testing, the platform completed nighttime flights over a two-kilometre route using lidar-based navigation alone, demonstrating its ability to operate without reliance on external signals.
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The partnership reflects broader efforts to scale commercial low-altitude logistics in China, where regulators and technology companies are increasingly supporting drone-based delivery to address urban congestion and labor constraints. Both companies said the collaboration would continue to focus on expanding use cases and improving the reliability of autonomous delivery systems.
