DEEP Robotics has introduced a new quadruped robot designed to look like a horse. It is based on the M20 Pro robot dog but features hoof-like feet and a redesigned body. The robot still uses the same technology for moving across rough terrain and performing inspection tasks.
The company is based in Hangzhou and focuses on industrial uses for its Lynx M20 family. These robots handle inspection, emergency rescue, logistics, and security patrol work. The horse-like version keeps the core motion control systems from the standard platform.
Design and Build Details
This special edition adds bionic legs and hoof-like feet to create a horse appearance while retaining practical functions. Reports put its weight at about 30 kg and its height at about 0.5 m. It carries a payload of up to 50 kg and runs on hot-swappable batteries for up to three hours.
The design includes 96-line LiDAR and SLAM navigation for obstacle avoidance. It holds an IP66 rating so it can work in rain, mud, and dust. Top speed reaches up to 5 m/s on suitable ground, though slower paces help with stability.
Intended Uses and Performance
The robot targets industrial inspection, security patrol, logistics, and emergency rescue scenarios. Its rugged build suits difficult terrain and hard-to-reach areas. Public reports frame it as a compact machine for carrying gear rather than a rideable model.
It was unveiled as a limited-edition Year of the Horse model tied to cultural timing. The machine can jump and navigate complex surfaces while keeping the same inspection capabilities as the base platform. Pricing sits around US$50,000 for this version.
Paths Forward / Looking Ahead
The special edition may serve mainly as a showcase for the company’s industrial quadruped technology. It could help draw broader interest by pairing biomimetic styling with field-ready performance. Continued work on the Lynx M20 family suggests more variants will appear in coming years.
Future updates might refine the stiff elements noted in early feedback while preserving core mobility. This approach keeps the focus on practical tasks rather than novelty alone. Overall the platform shows steady progress in adapting existing tech for varied environments.
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