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China’s Hesai adds colour to lidar as EV makers race to level up in self-driving tech

Colour-capable sensors to ‘significantly enhance’ sensing, helping cars identify traffic lights, construction signs, Deutsche Bank says

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Sun Kai, Hesai Group executive director, co-founder, and chief scientist, explains the company’s 6D technology on April 17, 2026 in Shanghai. Photo: Handout
Daniel Renin Shanghai
Hesai Group, the world’s largest maker of vehicle lidar sensors, introduced technology it said would raise autonomous driving features to a new level by detecting colour to improve the reliability of object identification.

The Shanghai-based maker of light ­detection and ranging ­sensors said its 6D full-colour platform would deliver lidar sensors with world-leading capabilities in ranging and small-target identification. 6D refers to the sensors’ ability to detect the X, Y and Z coordinates of an object, plus its reflectivity, velocity and colour.

Expected to hit the market in the second half of this year, the company’s ETX lidar sensors would be the first of their kind, according to Hesai CEO David Li Yifan.

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“This is not some kind of market hype,” he said in a media briefing on Friday. “It is a fundamental innovation, something that no one I know of has ever done before.”

He added that Hesai would prioritise “zero-to-one innovative breakthroughs” amid an intensified tech race in the global automotive industry, where key players were racing to develop driverless cars.

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“The technology eliminates the need for complex stitching or inference, meaning the autonomous driving system no longer needs to ‘guess’ when identifying critical coloured objects like traffic lights, lane lines or construction signs,” Deutsche Bank said in a research note over the weekend. The capability would “significantly enhance” the spatial intelligence of artificial intelligence world models, it added.

Hesai did not disclose which carmakers would take delivery of the first batch of ETX lidars. Li said the company was determined to bring down costs by increasing manufacturing capacity and capabilities.

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