Hesai Powers Safety-Certified AI Autonomy for Smart Logistics with 3D Lidar at MODEX 2026
At MODEX 2026, Hesai Technology showcased its JT128 lidar powering Thoro.ai's safety-certified AI autonomy platform for smart logistics robots.
- 30 mm
- 70% smaller than similar products
- 360° × 187°
What Happened
Hesai Technology (NASDAQ: HSAI; HKEX: 2525) attended MODEX 2026 in Atlanta to showcase its latest 3D lidar solutions for smart logistics. The company highlighted its collaboration with Thoro.ai, a Pittsburgh-based robotics firm, to supply the high-performance JT128 mini 3D lidar. This sensor will power Thoro.ai's perception platform across various robotic applications, including the industry's first safety-certified AI autonomy platform for industrial and commercial robots.
The JT128 features the world's widest 360° × 187° ultra-hemispherical field of view, providing all-around perception with no blind spots. Its slim 30 mm window height and 70% smaller volume compared to similar products allow easy integration into machines of all sizes. The lidar is highly reliable in challenging environments with reflective surfaces and glass, and it has passed 28 reliability tests.
“At Thoro.ai, we think about each of these OEM partnerships not just as standalone projects, but as part of our CoreFlex autonomy architecture: a modular, safety-certified platform designed to scale across many machine types.”
Why this matters
This collaboration simplifies the development of autonomous mobile robots, making it easier for manufacturers to deploy safe, intelligent machines in warehouses and logistics centers.
Terms in This Story
- Autonomous mobile robot (AMR)
- A robot that can move and perform tasks without human intervention, often used in warehouses.
- CoreFlex
- A unified sensor and software suite that helps OEMs develop autonomous solutions.
- Field of view (FOV)
- The extent of the observable world that a sensor can see at any moment.
Summarised from the linked release; details can be imperfect — always verify against the original source.